RGB-D salient object detection: A survey
Open accessAbstract
Salient object detection, which simulates human visual perception in locating the most significant object(s) in a scene, has been widely applied to various computer vision tasks. Now, the advent of depth sensors means that depth maps can easily be captured; this additional spatial information can boost the performance of salient object detection. Although various RGB-D based salient object detection models with promising performance have been proposed over the past several years, an in-depth understanding of these models and the challenges in this field remains lacking. In this paper, we provide a comprehensive survey of RGB-D based salient object detection models from various perspectives, and review related benchmark datasets in detail. Further, as light fields can also provide depth maps, we review salient object detection models and popular benchmark datasets from this domain too. Moreover, to investigate the ability of existing models to detect salient objects, we have carried out a comprehensive attribute-based evaluation of several representative RGB-D based salient object detection models. Finally, we discuss several challenges and open directions of RGB-D based salient object detection for future research. All collected models, benchmark datasets, datasets constructed for attribute-based evaluation, and related code are publicly available at https://github.com/taozh2017/RGBD-SODsurvey.
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Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, L., & Polosukhin, I. (2017) · arXiv · doi:10.48550/arxiv.1706.03762 · Cited by 120,404 · see citing works
Proceedings of IEEE Conference on Computer Vision and Pattern Recognition
(1993) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.1993.341010 · Cited by 14,474 · see citing works
Conditional Generative Adversarial Nets
Mirza, M., & Osindero, S. (2014) · arXiv · doi:10.48550/arxiv.1411.1784 · Cited by 8,863 · see citing works
Object Detection With Deep Learning: A Review
Zhao, Z.-Q., Zheng, P., Xu, S.-T., & Wu, X. (2019) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2018.2876865 · Cited by 5,545 · see citing works
Frequency-tuned salient region detection
Achanta, R., Hemami, S. S., Estrada, F., & Susstrunk, S. E. (2009) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2009.5206596 · Cited by 4,368 · see citing works
Residual Attention Network for Image Classification
Wang, F., Jiang, M., Qian, C., Yang, S., Li, C., Zhang, H., Wang, X., & Tang, X. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.683 · Cited by 4,073 · see citing works
Saliency Detection: A Spectral Residual Approach
Hou, X., & Zhang, L. (2007) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2007.383267 · Cited by 3,453 · see citing works
Unsupervised Monocular Depth Estimation with Left-Right Consistency
Godard, C., Aodha, O. M., & Brostow, G. J. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.699 · Cited by 3,270 · see citing works
Proceedings of the International Joint Conference on Artificial Intelligence 2007
Bundy, A. (2007) · International Joint Conference on Artificial Intelligence · Cited by 2,761 · see citing works
Saliency Detection via Graph-Based Manifold Ranking
Yang, C., Zhang, L., Lu, H., Ruan, X., & Yang, M.-H. (2013) · 2013 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2013.407 · Cited by 2,554 · see citing works
Proceedings of IEEE International Conference on Computer Vision
(1995) · doi:10.1109/iccv.1995 · Cited by 2,339 · see citing works
Saliency filters: Contrast based filtering for salient region detection
Perazzi, F., Krähenbühl, P., Pritch, Y., & Hornung, A. (2012) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2012.6247743 · Cited by 2,236 · see citing works
Structure-Measure: A New Way to Evaluate Foreground Maps
Fan, D.-P., Cheng, M.-M., Liu, Y., Li, T., & Borji, A. (2017) · 2017 IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2017.487 · Cited by 2,092 · see citing works
Self-citationPraNet: Parallel Reverse Attention Network for Polyp Segmentation
Fan, D.-P., Ji, G.-P., Zhou, T., Chen, G., Fu, H., Shen, J.-B., & Shao, L. (2020) · International Conference on Medical Image Computing and Computer-Assisted Intervention · doi:10.1007/978-3-030-59725-2_26 · Cited by 2,003 · see citing works
Self-citationHierarchical Saliency Detection
Yan, Q., Xu, L., Shi, J., & Jia, J. (2013) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2013.153 · Cited by 1,833 · see citing works
Enhanced-alignment Measure for Binary Foreground Map Evaluation
Fan, D.-P., Gong, C., Cao, Y. H., Ren, B., Cheng, M., & Borji, A. (2018) · International Joint Conference on Artificial Intelligence · doi:10.24963/ijcai.2018/97 · Cited by 1,690 · see citing works
Self-citationSalient Object Detection: A Benchmark
Borji, A., Cheng, M.-M., Jiang, H., & Li, J. (2015) · IEEE Transactions on Image Processing · doi:10.1109/tip.2015.2487833 · Cited by 1,550 · see citing works
Self-citationAMC: AutoML for Model Compression and Acceleration on Mobile Devices
He, Y., Lin, J., Liu, Z., Wang, H., Li, L.-J., & Han, S. (2018) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-01234-2_48 · Cited by 1,400 · see citing works
A large-scale hierarchical multi-view RGB-D object dataset
Lai, K., Bo, L., Ren, X., & Fox, D. (2011) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra.2011.5980382 · Cited by 1,339 · see citing works
EGNet: Edge Guidance Network for Salient Object Detection
Zhao, J., Liu, J., Fan, D.-P., Cao, Y. H., Yang, J., & Cheng, M. (2019) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2019.00887 · Cited by 1,285 · see citing works
Self-citationInf-Net: Automatic COVID-19 Lung Infection Segmentation From CT Images
Fan, D.-P., Zhou, T., Ji, G.-P., Zhou, Y., Chen, G., Fu, H., Shen, J., & Shao, L. (2020) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2020.2996645 · Cited by 1,262 · see citing works
Self-citationMedical Image Computing and Computer Assisted Intervention – MICCAI 2018
Frangi, A. F., Schnabel, J. A., Davatzikos, C. A., Alberola-López, C., & Fichtinger, G. (2018) · Lecture notes in computer science · doi:10.1007/978-3-030-00937-3 · Cited by 1,049 · see citing works
Deep Modular Co-Attention Networks for Visual Question Answering
Zhou, Y., Yu, J., Cui, Y., Tao, D., & Tian, Q. C. (2019) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2019.00644 · Cited by 1,013 · see citing works
Fan, D.-P., Ji, G.-P., Sun, G., Cheng, M., Shen, J., & Shao, L. (2020) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr42600.2020.00285 · Cited by 974 · see citing works
Self-citationAmulet: Aggregating Multi-level Convolutional Features for Salient Object Detection
Zhang, P., Wang, D., Lu, H., Wang, H., & Ruan, X. (2017) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2017.31 · Cited by 913 · see citing works
Deep convolutional neural fields for depth estimation from a single image
Liu, F., Shen, C., & Lin, G. (2015) · 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2015.7299152 · Cited by 892 · see citing works
A Survey of Model Compression and Acceleration for Deep Neural Networks
Cheng, Y., Wang, D., Zhou, P., & Zhang, T. (2017) · arXiv · doi:10.48550/arxiv.1710.09282 · Cited by 857 · see citing works
Salient Object Detection in the Deep Learning Era: An In-Depth Survey
Wang, W., Lai, Q., Fu, H., Shen, J., Ling, H., & Yang, R. (2021) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2021.3051099 · Cited by 827 · see citing works
Self-citationDeep Contrast Learning for Salient Object Detection
Li, G., & Yu, Y. (2016) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2016.58 · Cited by 793 · see citing works
Online Tracking by Learning Discriminative Saliency Map with Convolutional Neural NetworkPreprint
Hong, S., You, T., Kwak, S., & Han, B. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1502.06796 · Cited by 784 · see citing works
1Salient Object Detection: A Survey
Borji, A., Jiang, H., & Li, J. (2016) · Cited by 745 · see citing works
RGBD Salient Object Detection: A Benchmark and Algorithms
Peng, H., Li, B., Xiong, W., Hu, W., & Ji, R. (2014) · Lecture notes in computer science · doi:10.1007/978-3-319-10578-9_7 · Cited by 724 · see citing works
Rethinking RGB-D Salient Object Detection: Models, Data Sets, and Large-Scale Benchmarks
Fan, D.-P., Zheng, L. L., Zhang, Z., Zhu, M., & Cheng, M. (2020) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2020.2996406 · Cited by 711 · see citing works
Self-citationPyramid Feature Attention Network for Saliency Detection
Zhao, T., & Wu, X. (2019) · Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2019.00320 · Cited by 700 · see citing works
Deep Visual Attention Prediction
Wang, W., & Shen, J. (2017) · IEEE Transactions on Image Processing · doi:10.1109/tip.2017.2787612 · Cited by 671 · see citing works
Self-citationVideo Salient Object Detection via Fully Convolutional Networks
Wang, W., Shen, J., & Shao, L. (2017) · IEEE Transactions on Image Processing · doi:10.1109/tip.2017.2754941 · Cited by 635 · see citing works
Self-citationAdvanced Deep-Learning Techniques for Salient and Category-Specific Object Detection: A Survey
Han, J., Zhang, D., Cheng, G., Liu, N., & Xu, D. (2018) · IEEE Signal Processing Magazine · doi:10.1109/msp.2017.2749125 · Cited by 618 · see citing works
Proceedings of the 1987 International Conference on Neural Information Processing Systems
Anderson, D. (1987) · Cited by 612 · see citing works
Depth saliency based on anisotropic center-surround difference
Ju, R., Ge, L., Geng, W., Ren, T., & Wu, G. (2014) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2014.7025222 · Cited by 576 · see citing works
Leveraging stereopsis for saliency analysis
Niu, Y., Geng, Y., Li, X., & Liu, F. (2012) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2012.6247708 · Cited by 566 · see citing works
Salient Object Detection With Pyramid Attention and Salient Edges
Wang, W., Shuyang, Z., Shen, J., Hoi, S. C. H., & Borji, A. (2019) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2019.00154 · Cited by 563 · see citing works
Self-citationSee More, Know More: Unsupervised Video Object Segmentation With Co-Attention Siamese Networks
Lu, X., Wang, W., Ma, C., Shen, J., Shao, L., & Porikli, F. (2019) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2019.00374 · Cited by 536 · see citing works
Self-citationShifting More Attention to Video Salient Object Detection
Fan, D.-P., Wang, W., Cheng, M., & Shen, J. (2019) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2019.00875 · Cited by 528 · see citing works
Self-citationDepth-Induced Multi-Scale Recurrent Attention Network for Saliency Detection
Piao, Y., Ji, W., Li, J., Zhang, M., & Lu, H. (2019) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2019.00735 · Cited by 528 · see citing works
Salient object detection: A survey
Borji, A., Cheng, M.-M., Hou, Q., Jiang, H., & Li, J. (2019) · Computational Visual Media · doi:10.1007/s41095-019-0149-9 · Cited by 525 · see citing works
Self-citationPyramid Dilated Deeper ConvLSTM for Video Salient Object Detection
Song, H., Wang, W., Zhao, S., Shen, J., & Lam, K. (2018) · Lecture notes in computer science · doi:10.1007/978-3-030-01252-6_44 · Cited by 509 · see citing works
Self-citationCo-Saliency Detection via a Self-Paced Multiple-Instance Learning Framework
Zhang, D., Meng, D., & Han, J. (2016) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2016.2567393 · Cited by 508 · see citing works
JCS: An Explainable COVID-19 Diagnosis System by Joint Classification and Segmentation
Wu, Y.-H., Gao, S.-H., Mei, J., Xu, J., Fan, D.-P., Zhang, R.-G., & Cheng, M.-M. (2021) · IEEE Transactions on Image Processing · doi:10.1109/tip.2021.3058783 · Cited by 506 · see citing works
Self-citationSaliency Detection on Light Field
Li, N., Ye, J., Ji, Y., Ling, H., & Jingyi Yu, A. (2014) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2014.359 · Cited by 497 · see citing works
Saliency detection via Cellular Automata
Qin, Y., Lu, H., Xu, Y., & Wang, H. (2015) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2015.7298606 · Cited by 494 · see citing works
Learning Uncertain Convolutional Features for Accurate Saliency Detection
Zhang, P., Wang, D., Lu, H., Wang, H., & Yin, B. (2017) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2017.32 · Cited by 494 · see citing works
Saliency-Aware Video Object Segmentation
Wang, W., Shen, J., Yang, R., & Porikli, F. (2017) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2017.2662005 · Cited by 469 · see citing works
Self-citationA Stagewise Refinement Model for Detecting Salient Objects in Images
Wang, T., Borji, A., Zhang, L., Zhang, P., & Lu, H. (2017) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2017.433 · Cited by 466 · see citing works
Contrast Prior and Fluid Pyramid Integration for RGBD Salient Object Detection
Zhao, J.-X., Cao, Y. H., Fan, D.-P., Cheng, M., Li, X., & Zhang, L. (2019) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2019.00405 · Cited by 435 · see citing works
Self-citationUC-Net: Uncertainty Inspired RGB-D Saliency Detection via Conditional Variational Autoencoders
Zhang, J., Fan, D.-P., Dai, Y., Anwar, S., Saleh, F. S., Zhang, T., & Barnes, N. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr42600.2020.00861 · Cited by 423 · see citing works
Self-citationCNNs-Based RGB-D Saliency Detection via Cross-View Transfer and Multiview Fusion
Han, J., Chen, H., Liu, N., Yan, C. C., & Li, X. (2017) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2017.2761775 · Cited by 422 · see citing works
Review of Visual Saliency Detection With Comprehensive Information
Cong, R., Lei, J., Fu, H., Cheng, M., Lin, W., & Huang, Q. (2018) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2018.2870832 · Cited by 418 · see citing works
Self-citationHi-Net: Hybrid-Fusion Network for Multi-Modal MR Image Synthesis
Zhou, T., Fu, H., Chen, G., Shen, J., & Shao, L. (2020) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2020.2975344 · Cited by 400 · see citing works
Self-citationBBS-Net: RGB-D Salient Object Detection with a Bifurcated Backbone Strategy Network
Fan, D.-P., Zhai, Y., Borji, A., Yang, J., & Shao, L. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-58610-2_17 · Cited by 394 · see citing works
Self-citationJL-DCF: Joint Learning and Densely-Cooperative Fusion Framework for RGB-D Salient Object Detection
Fu, K., Fan, D.-P., Ji, G.-P., & Zhao, Q. (2020) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr42600.2020.00312 · Cited by 383 · see citing works
Self-citationDepth Enhanced Saliency Detection Method
Cheng, Y., Fu, H., Wei, X., Xiao, J., & Cao, X. (2014) · International Conference on Internet Multimedia Computing and Service · doi:10.1145/2632856.2632866 · Cited by 374 · see citing works
Chen, H., Li, Y., & Su, D. (2018) · Pattern Recognition · doi:10.1016/j.patcog.2018.08.007 · Cited by 368 · see citing works
RGBD Salient Object Detection via Deep Fusion
Qu, L., He, S., Zhang, J., Tian, J., Tang, Y., & Yang, Q. (2017) · IEEE Transactions on Image Processing · doi:10.1109/tip.2017.2682981 · Cited by 360 · see citing works
Hierarchical Question-Image Co-Attention for Visual Question Answering
Lu, J. (2024) · TIB Data Manager · doi:10.57702/uhdmfu1r · Cited by 357 · see citing works
Learning Selective Self-Mutual Attention for RGB-D Saliency Detection
Liu, N., Zhang, N., & Han, J. (2020) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr42600.2020.01377 · Cited by 355 · see citing works
Salient Objects in Clutter: Bringing Salient Object Detection to the Foreground
Fan, D.-P., Cheng, M., Liu, J., Gao, S., Hou, Q., & Borji, A. (2018) · Lecture notes in computer science · doi:10.1007/978-3-030-01267-0_12 · Cited by 351 · see citing works
Self-citationProgressively Complementarity-Aware Fusion Network for RGB-D Salient Object Detection
Chen, H., & Li, Y. (2018) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2018.00322 · Cited by 349 · see citing works
SalGAN: Visual Saliency Prediction with Generative Adversarial NetworksPreprint
Pan, J., Canton-Ferrer, C., McGuinness, K., O'Connor, N. E., Torres, J., Sayrol, E., & Giró-i-Nieto, X. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1701.01081 · Cited by 337 · see citing works
Three-Stream Attention-Aware Network for RGB-D Salient Object Detection
Chen, H., & Li, Y. (2019) · IEEE Transactions on Image Processing · doi:10.1109/tip.2019.2891104 · Cited by 323 · see citing works
Contour Knowledge Transfer for Salient Object Detection
Li, X., Yang, F., Cheng, H., Liu, W., & Shen, D. G. (2018) · Lecture notes in computer science · doi:10.1007/978-3-030-01267-0_22 · Cited by 309 · see citing works
Real-Time Salient Object Detection with a Minimum Spanning Tree
Tu, W.-C., He, S., Yang, Q., & Chien, S. (2016) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2016.256 · Cited by 300 · see citing works
A Single Stream Network for Robust and Real-Time RGB-D Salient Object Detection
Zhao, X., Zhang, L., Pang, Y., Lu, H., & Lei Zhang, A. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-58542-6_39 · Cited by 292 · see citing works
RGB-T Image Saliency Detection via Collaborative Graph Learning
Tu, Z., Xia, T., Li, C., Wang, X., Ma, Y., & Tang, J. (2019) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2019.2924578 · Cited by 276 · see citing works
Zhou, T., Thung, K., Zhu, X., & Shen, D. G. (2018) · Human Brain Mapping · doi:10.1002/hbm.24428 · Cited by 270 · see citing works
Self-citationRGBT Salient Object Detection: A Large-Scale Dataset and Benchmark
Tu, Z., Ma, Y., Li, Z., Li, C., Xu, J., & Liu, Y. (2022) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2022.3171688 · Cited by 268 · see citing works
Hierarchical Dynamic Filtering Network for RGB-D Salient Object Detection
Pang, Y., Zhang, L., Zhao, X., & Lu, H. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-58595-2_15 · Cited by 265 · see citing works
Multi-View Learning With Incomplete Views
Xu, C., Tao, D., & Xu, C. (2015) · IEEE Transactions on Image Processing · doi:10.1109/tip.2015.2490539 · Cited by 264 · see citing works
A2dele: Adaptive and Attentive Depth Distiller for Efficient RGB-D Salient Object Detection
Piao, Y., Rong, Z., Zhang, M., Ren, W., & Lu, H. (2020) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr42600.2020.00908 · Cited by 262 · see citing works
Adaptive Fusion for RGB-D Salient Object Detection
Wang, N., & Gong, X. (2019) · IEEE Access · doi:10.1109/access.2019.2913107 · Cited by 258 · see citing works
ICNet: Information Conversion Network for RGB-D Based Salient Object Detection
Li, G., Liu, Z., & Ling, H. (2020) · IEEE Transactions on Image Processing · doi:10.1109/tip.2020.2976689 · Cited by 252 · see citing works
DPANet: Depth Potentiality-Aware Gated Attention Network for RGB-D Salient Object Detection
Chen, Z., Cong, R., Xu, Q., & Huang, Q. (2020) · IEEE Transactions on Image Processing · doi:10.1109/tip.2020.3028289 · Cited by 251 · see citing works
Multi-Interactive Dual-Decoder for RGB-Thermal Salient Object Detection
Tu, Z., Li, Z., Li, C., Lang, Y., & Tang, J. (2021) · IEEE Transactions on Image Processing · doi:10.1109/tip.2021.3087412 · Cited by 248 · see citing works
RGB-T Salient Object Detection via Fusing Multi-Level CNN Features
Zhang, Q., Huang, N., Yao, L., Zhang, D., Shan, C., & Han, J. (2020) · IEEE Transactions on Image Processing · doi:10.1109/tip.2019.2959253 · Cited by 247 · see citing works
ASIF-Net: Attention Steered Interweave Fusion Network for RGB-D Salient Object Detection
Li, C., Cong, R., Kwong, S., Hou, J., Fu, H., Zhu, G., Zhang, D., & Huang, Q. (2020) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2020.2969255 · Cited by 245 · see citing works
Song, H., Liu, Z., Du, H., Sun, G., Meur, O. L., & Ren, T. (2017) · IEEE Transactions on Image Processing · doi:10.1109/tip.2017.2711277 · Cited by 242 · see citing works
Select, Supplement and Focus for RGB-D Saliency Detection
Zhang, M., Ren, W., Piao, Y., Rong, Z., & Lu, H. (2020) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr42600.2020.00353 · Cited by 242 · see citing works
Saliency-based discriminant tracking
Mahadevan, V., & Vasconcelos, N. M. (2009) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2009.5206573 · Cited by 241 · see citing works
Cong, R., Lei, J., Zhang, C., Huang, Q., Cao, X., & Hou, C. (2016) · IEEE Signal Processing Letters · doi:10.1109/lsp.2016.2557347 · Cited by 235 · see citing works
Local Background Enclosure for RGB-D Salient Object Detection
Feng, D. D., Barnes, N. M., You, S., & McCarthy, C. D. (2016) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2016.257 · Cited by 226 · see citing works
Zhou, T., Liu, M., Thung, K., & Shen, D. G. (2019) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2019.2913158 · Cited by 226 · see citing works
Self-citationExploiting global priors for RGB-D saliency detection
Ren, J., Gong, X., Yu, L., Zhou, W., & Yang, M. Y. (2015) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw.2015.7301391 · Cited by 221 · see citing works
Selectivity or Invariance: Boundary-Aware Salient Object Detection
Su, J., Li, J., Zhang, Y., Xia, C., & Tian, Y. (2019) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2019.00390 · Cited by 221 · see citing works
Person Re-Identification by Saliency Learning
Zhao, R., Oyang, W., & Wang, X. (2016) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2016.2544310 · Cited by 211 · see citing works
Bilateral Attention Network for RGB-D Salient Object Detection
Zhang, Z., Lin, Z., Xu, J., Jin, W.-D., Lu, S.-P., & Fan, D.-P. (2021) · IEEE Transactions on Image Processing · doi:10.1109/tip.2021.3049959 · Cited by 210 · see citing works
Self-citationAdversarial Robustness: From Self-Supervised Pre-Training to Fine-Tuning
Chen, T., Liu, S., Chang, S., Cheng, Y., Amini, L., & Wang, Z. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr42600.2020.00078 · Cited by 205 · see citing works
Accurate RGB-D Salient Object Detection via Collaborative Learning
Ji, W., Li, J., Zhang, M., Piao, Y., & Lu, H. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-58523-5_4 · Cited by 204 · see citing works
Multi-Source Weak Supervision for Saliency Detection
Zeng, Y., Zhuge, Y., Lu, H., Zhang, L., Qian, M., & Yu, Y. (2019) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2019.00623 · Cited by 203 · see citing works
RGB-T Saliency Detection Benchmark: Dataset, Baselines, Analysis and a Novel Approach
Wang, G., Li, C., Ma, Y., Zheng, A., Tang, J., & Luo, B. (2018) · Communications in computer and information science · doi:10.1007/978-981-13-1702-6_36 · Cited by 202 · see citing works
RGBD salient object detection via deep fusion
Qu, L., He, S., Zhang, J., Tian, J., Tang, Y., & Yang, Q. (2017) · Singapore Management University Institutional Knowledge (InK) (Singapore Management University) · Cited by 195 · see citing works
A Three-Pathway Psychobiological Framework of Salient Object Detection Using Stereoscopic Technology
Li, G., & Zhu, C. (2017) · IEEE International Conference on Computer Vision Workshops · doi:10.1109/iccvw.2017.355 · Cited by 184 · see citing works
Depth really Matters: Improving Visual Salient Region Detection with Depth
Desingh, K., Madhava Krishna, K., Rajan, D., & Jawahar, C. V. (2013) · British Machine Vision Conference (BMVC) · doi:10.5244/c.27.98 · Cited by 182 · see citing works
Cross-Modal Weighting Network for RGB-D Salient Object Detection
Li, G., Liu, Z., Ye, L., Wang, Y., & Ling, H. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-58520-4_39 · Cited by 182 · see citing works
Supervision by Fusion: Towards Unsupervised Learning of Deep Salient Object Detector
Zhang, D., Han, J., & Zhang, Y. (2017) · IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2017.436 · Cited by 175 · see citing works
PDNet: Prior-Model Guided Depth-Enhanced Network for Salient Object Detection
Zhu, C., Cai, X., Huang, K., Li, T. H., & Li, G. (2019) · IEEE International Conference on Multimedia and Expo (ICME) · doi:10.1109/icme.2019.00042 · Cited by 173 · see citing works
Salient object detection for RGB-D image by single stream recurrent convolution neural network
Liu, Z., Shi, S. X., Duan, Q., Zhang, W., & Zhao, P. (2019) · Neurocomputing · doi:10.1016/j.neucom.2019.07.012 · Cited by 172 · see citing works
Progressively Guided Alternate Refinement Network for RGB-D Salient Object Detection
Chen, S., & Fu, Y. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-58598-3_31 · Cited by 165 · see citing works
RGB-D Salient Object Detection with Cross-Modality Modulation and Selection
Li, C., Cong, R., Piao, Y., Xu, Q., & Loy, C. C. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-58598-3_14 · Cited by 160 · see citing works
An Innovative Salient Object Detection Using Center-Dark Channel Prior
Zhu, C., Li, G., Wang, W., & Wang, R. (2017) · IEEE International Conference on Computer Vision Workshops · doi:10.1109/iccvw.2017.178 · Cited by 153 · see citing works
Going From RGB to RGBD Saliency: A Depth-Guided Transformation Model
Cong, R., Lei, J., Fu, H., Hou, J., Huang, Q., & Kwong, S. (2019) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2019.2932005 · Cited by 149 · see citing works
Salient object detection for RGB-D image via saliency evolution
Guo, J., Ren, T., & Bei, J. (2016) · IEEE International Conference on Multimedia and Expo (ICME) · doi:10.1109/icme.2016.7552907 · Cited by 147 · see citing works
SG-NN: Sparse Generative Neural Networks for Self-Supervised Scene Completion of RGB-D Scans
Dai, A., Diller, C., & Nießner, M. (2020) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr42600.2020.00093 · Cited by 147 · see citing works
Dense saliency-based spatiotemporal feature points for action recognition
Rapantzikos, K. E., Avrithis, Y., & Kollias, S. (2009) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2009.5206525 · Cited by 144 · see citing works
Pairwise Body-Part Attention for Recognizing Human-Object Interactions
Fang, H.-S., Cao, J., Tai, Y., & Lu, C. (2018) · Lecture notes in computer science · doi:10.1007/978-3-030-01249-6_4 · Cited by 144 · see citing works
Re-thinking Co-Salient Object Detection
Fan, D.-P., Li, T., Zheng, L. L., Ji, G.-P., Zhang, D., Cheng, M., Fu, H., & Shen, J. (2021) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2021.3060412 · Cited by 144 · see citing works
Self-citationA weighted sparse coding framework for saliency detection
Li, N., Sun, B., & Yu, J. (2015) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2015.7299158 · Cited by 143 · see citing works
Global and Local-Contrast Guides Content-Aware Fusion for RGB-D Saliency Prediction
Zhou, W., Lv, Y., Lei, J., & Yu, L. (2019) · IEEE Transactions on Systems Man and Cybernetics Systems · doi:10.1109/tsmc.2019.2957386 · Cited by 143 · see citing works
Distinct Class-Specific Saliency Maps for Weakly Supervised Semantic Segmentation
Shimoda, W., & Yanai, . (2016) · Lecture notes in computer science · doi:10.1007/978-3-319-46493-0_14 · Cited by 140 · see citing works
SDC-Depth: Semantic Divide-and-Conquer Network for Monocular Depth Estimation
Wang, L., Zhang, J., Wang, O., Lin, Z., & Lu, H. (2020) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr42600.2020.00062 · Cited by 140 · see citing works
Salient Object Detection via Multiple Instance Learning
Huang, F. L., Qi, J., Lu, H., Zhang, L., & Ruan, X. (2017) · IEEE Transactions on Image Processing · doi:10.1109/tip.2017.2669878 · Cited by 138 · see citing works
Cong, R., Lei, J., Fu, H., Huang, Q., Cao, X., & Hou, C. (2017) · IEEE Transactions on Image Processing · doi:10.1109/tip.2017.2763819 · Cited by 136 · see citing works
Unsupervised Object Class Discovery via Saliency-Guided Multiple Class Learning
Zhu, J.-Y., Wu, J., Xu, Y. L., Chang, E., & Zhuowen Tu, A. (2014) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2014.2353617 · Cited by 135 · see citing works
Semi-Supervised Video Salient Object Detection Using Pseudo-Labels
Yan, P., Li, G., Xie, Y., Li, Z., Wang, C., Chen, T., & Lin, L. (2019) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2019.00738 · Cited by 135 · see citing works
Joint Learning of Saliency Detection and Weakly Supervised Semantic Segmentation
Zeng, Y., Zhuge, Y., Lu, H., & Zhang, L. (2019) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2019.00732 · Cited by 132 · see citing works
Salient Region Detection via Integrating Diffusion-Based Compactness and Local Contrast
Zhou, L. J., Yang, Z., Yuan, Q., Zhou, Z., & Hu, D. (2015) · IEEE Transactions on Image Processing · doi:10.1109/tip.2015.2438546 · Cited by 131 · see citing works
Light Field Saliency Detection With Deep Convolutional Networks
Zhang, J., Liu, Y., Zhang, S., Poppe, R. W., & Wang, M. (2020) · IEEE Transactions on Image Processing · doi:10.1109/tip.2020.2970529 · Cited by 131 · see citing works
Joint Learning of Saliency Detection and Weakly Supervised Semantic SegmentationPreprint
Zeng, Y., Zhuge, Y., Lu, H., & Zhang, L. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1909.04161 · Cited by 127 · see citing works
Ciptadi, A., Hermans, T., & Rehg, J. M. (2013) · British Machine Vision Conference (BMVC) · doi:10.5244/c.27.112 · Cited by 124 · see citing works
Deep Learning for Light Field Saliency Detection
Wang, T., Piao, Y., Lu, H., Li, X., & Zhang, L. (2019) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2019.00893 · Cited by 124 · see citing works
An Iterative Co-Saliency Framework for RGBD Images
Cong, R., Lei, J., Fu, H., Lin, W., Huang, Q., Cao, X., & Hou, C. (2017) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2017.2771488 · Cited by 123 · see citing works
Cascade Graph Neural Networks for RGB-D Salient Object Detection
Luo, A., Li, X., Yang, F., Jiao, Z., Cheng, H., & Lyu, S. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-58610-2_21 · Cited by 119 · see citing works
Asymmetric Two-Stream Architecture for Accurate RGB-D Saliency Detection
Zhang, M., Fei, S. X., Liu, J., Xu, S., Piao, Y., & Lu, H. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-58604-1_23 · Cited by 119 · see citing works
Multi-Level Context Ultra-Aggregation for Stereo Matching
Nie, G.-Y., Cheng, M., Liu, Y., Liang, Z., Fan, D.-P., Liu, Y., & Wang, Y. (2019) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2019.00340 · Cited by 117 · see citing works
Self-citationA Review of Co-Saliency Detection Algorithms
Zhang, D., Fu, H., Han, J., Borji, A., & Li, X. (2018) · ACM Transactions on Intelligent Systems and Technology · doi:10.1145/3158674 · Cited by 116 · see citing works
LFNet: Light Field Fusion Network for Salient Object Detection
Zhang, M., Ji, W., Piao, Y., Li, J., Zhang, Y., Xu, S., & Lu, H. (2020) · IEEE Transactions on Image Processing · doi:10.1109/tip.2020.2990341 · Cited by 116 · see citing works
Dual Refinement Underwater Object Detection Network
Fan, B., Chen, W., Cong, Y., & Tian, J. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-58565-5_17 · Cited by 115 · see citing works
Zhou, T., Thung, K., Liu, M., Shi, F., Zhang, C., & Shen, D. G. (2019) · Medical Image Analysis · doi:10.1016/j.media.2019.101630 · Cited by 109 · see citing works
Self-citationDepth-Quality-Aware Salient Object Detection
Chen, C., Wei, J., Peng, C., & Qin, H. (2021) · IEEE Transactions on Image Processing · doi:10.1109/tip.2021.3052069 · Cited by 109 · see citing works
Chen, C., Wei, J., Peng, C., Zhang, W., & Qin, H. (2020) · IEEE Transactions on Image Processing · doi:10.1109/tip.2020.2968250 · Cited by 106 · see citing works
HSCS: Hierarchical Sparsity Based Co-saliency Detection for RGBD Images
Cong, R., Lei, J., Fu, H., Huang, Q., Cao, X., & Ling, N. (2018) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2018.2884481 · Cited by 103 · see citing works
Saliency Detection on Light Field
Li, N., Ye, J., Ji, Y., Ling, H., & Jingyi Yu, A. (2016) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2016.2610425 · Cited by 101 · see citing works
Kernelized Saliency-Based Person Re-Identification Through Multiple Metric Learning
Martinel, N., Micheloni, C., & Foresti, G. L. (2015) · IEEE Transactions on Image Processing · doi:10.1109/tip.2015.2487048 · Cited by 100 · see citing works
M3S-NIR: Multi-modal Multi-scale Noise-Insensitive Ranking for RGB-T Saliency Detection
Tu, Z., Xia, T., Li, C., Lu, Y., & Tang, J. (2019) · IEEE International Conference on Multimedia Information Processing and Retrieval (MIPR) · doi:10.1109/mipr.2019.00032 · Cited by 100 · see citing works
Saliency Detection on Light Field
Zhang, J., Wang, M., Lin, L., Yang, X., Gao, J., & Rui, Y. (2017) · ACM Transactions on Multimedia Computing Communications and Applications · doi:10.1145/3107956 · Cited by 99 · see citing works
RGBD Salient Object Detection via Disentangled Cross-Modal Fusion
Chen, H., Deng, Y., Li, Y., Hung, T.-Y., & Lin, G. (2020) · IEEE Transactions on Image Processing · doi:10.1109/tip.2020.3014734 · Cited by 98 · see citing works
cmSalGAN: RGB-D Salient Object Detection With Cross-View Generative Adversarial Networks
Jiang, B., Zhou, Z., Wang, X., Tang, J., & Luo, B. (2020) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2020.2997184 · Cited by 95 · see citing works
Data-Level Recombination and Lightweight Fusion Scheme for RGB-D Salient Object Detection
Wang, X., Li, S., Chen, C., Fang, Y., Hao, A., & Qin, H. (2020) · IEEE Transactions on Image Processing · doi:10.1109/tip.2020.3037470 · Cited by 91 · see citing works
Xia, C., Li, J., Chen, X., Zheng, A., & Zhang, Y. (2017) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2017.468 · Cited by 90 · see citing works
Zhang, D., Meng, D., Zhao, L., & Han, J. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1703.01290 · Cited by 86 · see citing works
Memory-oriented Decoder for Light Field Salient Object Detection
Zhang, M., Li, J., Ji, W., Piao, Y., & Lu, H. (2019) · neural information processing systems · Cited by 84 · see citing works
Shigematsu, R., Feng, D. D., You, S., & Barnes, N. M. (2017) · IEEE International Conference on Computer Vision Workshops · doi:10.1109/iccvw.2017.323 · Cited by 83 · see citing works
Salient region detection for stereoscopic images
Fan, X., Liu, Z., & Sun, G. (2014) · doi:10.1109/icdsp.2014.6900706 · Cited by 82 · see citing works
RGB-D Salient Object Detection via Minimum Barrier Distance Transform and Saliency Fusion
Wang, A., & Wang, M. (2017) · IEEE Signal Processing Letters · doi:10.1109/lsp.2017.2688136 · Cited by 82 · see citing works
Is Depth Really Necessary for Salient Object Detection?
Zhao, J., Zhao, Y., Li, J., & Chen, X. (2020) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3394171.3413855 · Cited by 76 · see citing works
Geometric Structure Based and Regularized Depth Estimation From 360 Indoor Imagery
Jin, L., Xu, Y., Zheng, J., Zhang, J., Tang, R., Xu, S., Jingyi Yu, A., & Gao, S. (2020) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr42600.2020.00097 · Cited by 74 · see citing works
Piao, Y., Rong, Z., Zhang, M., & Lu, H. (2020) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v34i07.6860 · Cited by 69 · see citing works
Saliency Detection via Depth-Induced Cellular Automata on Light Field
Piao, Y., Li, X., Zhang, M., Jingyi Yu, A., & Lu, H. (2019) · IEEE Transactions on Image Processing · doi:10.1109/tip.2019.2942434 · Cited by 64 · see citing works
Saliency detection with a deeper investigation of light field
Zhang, J., Wang, M., Gao, J., Wang, Y., Zhang, X., & Wu, X. (2015) · International Conference on Artificial Intelligence · Cited by 63 · see citing works
Nguyen, T., Zhao, Q., & Yan, S. (2017) · International Journal of Computer Vision · doi:10.1007/s11263-017-1042-6 · Cited by 63 · see citing works
Deep Light-field-driven Saliency Detection from a Single View
Piao, Y., Rong, Z., Zhang, M., Li, X., & Lu, H. (2019) · International Joint Conference on Artificial Intelligence · doi:10.24963/ijcai.2019/127 · Cited by 61 · see citing works
A Model of Visual Attention for Natural Image Retrieval
Liu, G., & Fan, D.-P. (2013) · International Conference on Information Science and Cloud Computing Companion (ISCC-C) · doi:10.1109/iscc-c.2013.21 · Cited by 58 · see citing works
Self-citationDepth-aware saliency detection using convolutional neural networks
Ding, Y. C., Liu, Z., Huang, M., Shi, R., & Wang, X. (2019) · Journal of Visual Communication and Image Representation · doi:10.1016/j.jvcir.2019.03.019 · Cited by 57 · see citing works
Liu, Z., Zhang, W., & Zhao, P. (2020) · Neurocomputing · doi:10.1016/j.neucom.2020.01.045 · Cited by 57 · see citing works
Stereoscopic saliency model using contrast and depth-guided-background prior
Liang, F., Duan, L., Ma, W., Qiao, Y., Cai, Z., & Qing, L. (2017) · Neurocomputing · doi:10.1016/j.neucom.2017.10.052 · Cited by 55 · see citing works
300-FPS Salient Object Detection via Minimum Directional Contrast
Huang, X., & Zhang, Y. (2017) · IEEE Transactions on Image Processing · doi:10.1109/tip.2017.2710636 · Cited by 54 · see citing works
Zhang, M., Zhang, Y., Piao, Y., Hu, B., & Lu, H. (2020) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3394171.3413969 · Cited by 53 · see citing works
Semi-Supervised Salient Object Detection Using a Linear Feedback Control System Model
Zhou, Y., Huo, S., Xiang, W., Hou, C., & Kung, S. (2018) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2018.2793278 · Cited by 52 · see citing works
Chen, H., Li, Y., & Su, D. (2019) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2019.2934986 · Cited by 44 · see citing works
Proceedings of the 33rd international conference on Pattern recognition
Mester, R., & Felsberg, M. (2011) · Cited by 41 · see citing works
Attention-guided RGBD saliency detection using appearance information
Zhou, X., Li, G., Gong, C., Liu, Z., & Zhang, J. (2020) · Image and Vision Computing · doi:10.1016/j.imavis.2020.103888 · Cited by 38 · see citing works
Multi-level cross-modal interaction network for RGB-D salient object detection
Huang, Z., Chen, H., Zhou, T., Yun-zhi, Y., & Liu, B. (2021) · Neurocomputing · doi:10.1016/j.neucom.2021.04.053 · Cited by 37 · see citing works
Self-citationAttention-Aware Cross-Modal Cross-Level Fusion Network for RGB-D Salient Object Detection
Chen, H., Li, Y., & Su, D. (2018) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros.2018.8594373 · Cited by 36 · see citing works
RGBD Salient Object Detection using Spatially Coherent Deep Learning Framework
Huang, P., Shen, C.-H., & Hsiao, H.-F. (2018) · IEEE International Conference on Digital Signal Processing (DSP) · doi:10.1109/icdsp.2018.8631584 · Cited by 36 · see citing works
GFNet: Gate Fusion Network With Res2Net for Detecting Salient Objects in RGB-D Images
Zhou, W., Chen, Y., Liu, C., & Yu, L. (2020) · IEEE Signal Processing Letters · doi:10.1109/lsp.2020.2993471 · Cited by 35 · see citing works
RGBT Salient Object Detection: A Large-scale Dataset and BenchmarkPreprint
Tu, Z., Ma, Y., Li, Z., et al. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2007.03262 · Cited by 34 · see citing works
Learning-based saliency model with depth information
Ma, C., & Hang, H. (2015) · Journal of Vision · doi:10.1167/15.6.19 · Cited by 33 · see citing works
A Two-Stage Bayesian Integration Framework for Salient Object Detection on Light Field
Wang, A., Wang, M., Li, X., Mi, Z., & Zhou, H. (2017) · Neural Processing Letters · doi:10.1007/s11063-017-9610-x · Cited by 33 · see citing works
RGB-D Salient Object Detection by a CNN With Multiple Layers Fusion
Huang, R., Xing, Y. T., & Wang, Z. (2019) · IEEE Signal Processing Letters · doi:10.1109/lsp.2019.2898508 · Cited by 33 · see citing works
Salient object detection in RGB-D image based on saliency fusion and propagation
Guo, J., Ren, T., Bei, J., & Zhu, Y. (2015) · International Conference on Internet Multimedia Computing and Service · doi:10.1145/2808492.2808551 · Cited by 32 · see citing works
Relative location for light field saliency detection
Sheng, H., Zhang, S., Liu, X., & Xiong, Z. (2016) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.2016.7471953 · Cited by 31 · see citing works
Improving RGBD Saliency Detection Using Progressive Region Classification and Saliency Fusion
Du, H., Liu, Z., Song, H., Mei, L., & Xu, Z. (2016) · IEEE Access · doi:10.1109/access.2016.2632724 · Cited by 30 · see citing works
Language-aware weak supervision for salient object detection
Qian, M., Qi, J., Zhang, L., Feng, M., & Lu, H. (2019) · Pattern Recognition · doi:10.1016/j.patcog.2019.06.021 · Cited by 30 · see citing works
Learning Multiscale Deep Features and SVM Regressors for Adaptive RGB-T Saliency Detection
Ma, Y., Sun, D., Meng, Q., Ding, Z., & Li, C. (2017) · International Symposium on Computational Intelligence and Design · doi:10.1109/iscid.2017.92 · Cited by 29 · see citing works
CNN-Based RGB-D Salient Object Detection: Learn, Select, and Fuse
Chen, H., Li, Y., Deng, Y., & Lin, G. (2021) · International Journal of Computer Vision · doi:10.1007/s11263-021-01452-0 · Cited by 29 · see citing works
Water flow driven salient object detection at 180 fps
Huang, X., & Zhang, Y. (2017) · Pattern Recognition · doi:10.1016/j.patcog.2017.10.027 · Cited by 28 · see citing works
Depth incorporating with color improves salient object detection
Tang, Y., Tong, R., Tang, M., & Zhang, Y. (2015) · The Visual Computer · doi:10.1007/s00371-014-1059-6 · Cited by 27 · see citing works
Bio-Inspired Computing - Theories and Applications
(2014) · Communications in computer and information science · doi:10.1007/978-3-662-45049-9 · Cited by 27 · see citing works
Region-based depth feature descriptor for saliency detection on light field
Wang, X., Dong, Y., Zhang, Q., & Wang, Q. (2020) · Multimedia Tools and Applications · doi:10.1007/s11042-020-08890-x · Cited by 25 · see citing works
Lei, J., Zhang, H., You, L., Hou, C., & Wang, L. (2013) · Neurocomputing · doi:10.1016/j.neucom.2012.08.057 · Cited by 23 · see citing works
A Large Scale RGB-D Dataset for Action Recognition
Zhang, J., Li, W., Wang, P., Ogunbona, P., Liu, S., & Tang, C. (2018) · Lecture notes in computer science · doi:10.1007/978-3-319-91863-1_8 · Cited by 22 · see citing works
Multi-Scale Adversarial Feature Learning for Saliency Detection
Zhu, D., Dai, L., Luo, Y., Zhang, G., Shao, X., Itti, L., & Lu, J. (2018) · Symmetry · doi:10.3390/sym10100457 · Cited by 18 · see citing works
Depth-aware saliency detection using discriminative saliency fusion
Song, H., Liu, Z., Du, H., & Sun, G. (2016) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.2016.7471952 · Cited by 17 · see citing works
A Unified RGB-T Saliency Detection Benchmark: Dataset, Baselines, Analysis and A Novel ApproachPreprint
Li, C., Wang, G., Ma, Y., Zheng, A., Luo, B., & Tang, J. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1701.02829 · Cited by 17 · see citing works
Salience Guided Depth Calibration for Perceptually Optimized Compressive Light Field 3D Display
Wang, S., Liao, W., Surman, P., Tu, Z., Zheng, Y., & Yuan, J. (2018) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2018.00217 · Cited by 17 · see citing works
CoCNN: RGB-D deep fusion for stereoscopic salient object detection
Liang, F., Duan, L., Ma, W., Qiao, Y., Cai, Z., Miao, J., & Ye, Q. (2020) · Pattern Recognition · doi:10.1016/j.patcog.2020.107329 · Cited by 17 · see citing works
Salient regions detection for indoor robots using RGB-D data
Jiang, L., Koch, A., & Zell, A. (2015) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra.2015.7139362 · Cited by 16 · see citing works
Saliency analysis based on depth contrast increased
Sheng, H., Liu, X., & Zhang, S. (2016) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.2016.7471896 · Cited by 16 · see citing works
Multi-interactive Encoder-decoder Network for RGBT Salient Object Detection.
Tu, Z., Li, Z., Li, C., Lang, Y., & Tang, J. (2020) · Cited by 15 · see citing works
Salient object detection for RGB-D images by generative adversarial network
Liu, Z., Tang, J., Xiang, Q., & Zhao, P. (2020) · Multimedia Tools and Applications · doi:10.1007/s11042-020-09188-8 · Cited by 15 · see citing works
Triple-Complementary Network for RGB-D Salient Object Detection
Huang, R., Xing, Y. T., & Zou, Y. (2020) · IEEE Signal Processing Letters · doi:10.1109/lsp.2020.2989674 · Cited by 14 · see citing works
Chen, H., Li, Y., & Su, D. (2017) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros.2017.8206370 · Cited by 13 · see citing works
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- [46][46] Lang C Y Nguyen T V Katti H Yadati K Kankanhalli M Yan S C Fitzgibbon A Lazebnik S Perona P Sato Y Schmid C Depth matters: influence of depth cues on visual saliency Computer Vision — ECCV 2012. Lecture Notes in Computer Science, Vol. 7573 2012 Berlin Heidelberg Springer 101 115
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Artificial intelligence in the creative industries: a review
Anantrasirichai, N., & Bull, D. (2022) · Artificial Intelligence Review · doi:10.1007/s10462-021-10039-7 · Cited by 793 · see citing works
Liu, N., Zhang, N., Wan, K.-Y., Shao, L., & Han, J.-W. (2021) · IEEE International Conference on Computer Vision · doi:10.1109/iccv48922.2021.00468 · Cited by 520 · see citing works
Self-citationBayoudh, K., Knani, R., Hamdaoui, F., & Mtibaa, A. (2022) · The Visual Computer · doi:10.1007/s00371-021-02166-7 · Cited by 456 · see citing works
Cross-level Feature Aggregation Network for Polyp Segmentation
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Adhanom, I. B., MacNeilage, P. R., & Folmer, E. (2023) · Virtual Reality · doi:10.1007/s10055-022-00738-z · Cited by 346 · see citing works
Calibrated RGB-D Salient Object Detection
Ji, W., Li, J., Yu, S., Zhang, M., Piao, Y., Yao, S., Bi, Q., Ma, K., Zheng, Y., Lu, H., et al. (2021) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr46437.2021.00935 · Cited by 302 · see citing works
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Tang, H., Li, Z., Zhang, D., He, S., & Tang, J. (2024) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2024.3511621 · Cited by 259 · see citing works
A comprehensive survey of deep learning-based lightweight object detection models for edge devices
Mittal, P. (2024) · Artificial Intelligence Review · doi:10.1007/s10462-024-10877-1 · Cited by 244 · see citing works
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Pang, Y., Zhao, X., Zhang, L., & Lu, H. (2023) · IEEE Transactions on Image Processing · doi:10.1109/tip.2023.3234702 · Cited by 238 · see citing works
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Zhou, W., Zhu, Y., Lei, J., Wan, J., & Yu, L. (2021) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2021.3077767 · Cited by 229 · see citing works
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Self-citationZhou, X., Shen, K., Weng, L., Cong, R., Zheng, B., Zhang, J., & Yan, C. (2022) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2022.3163152 · Cited by 203 · see citing works
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Yuan, M., Shi, X., Wang, N., Wang, Y., & Wei, X. (2024) · Information Fusion · doi:10.1016/j.inffus.2024.102246 · Cited by 188 · see citing works
MobileSal: Extremely Efficient RGB-D Salient Object Detection
Wu, Y.-H., Liu, Y., Xu, J., Bian, J.-W., Gu, Y.-C., & Cheng, M.-M. (2022) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2021.3134684 · Cited by 176 · see citing works
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Cheng, M., & Fan, D.-P. (2021) · International Journal of Computer Vision · doi:10.1007/s11263-021-01490-8 · Cited by 173 · see citing works
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Zhai, Y., Fan, D.-P., Yang, J., Borji, A., Shao, L., Han, J., & Wang, L. (2021) · IEEE Transactions on Image Processing · doi:10.1109/tip.2021.3116793 · Cited by 171 · see citing works
Self-citationHiDAnet: RGB-D Salient Object Detection via Hierarchical Depth Awareness
Wu, Z., Allibert, G., Mériaudeau, F., Ma, C., & Demonceaux, C. (2023) · IEEE Transactions on Image Processing · doi:10.1109/tip.2023.3263111 · Cited by 163 · see citing works
Jin, X. H., Yi, K., & Xu, J. (2022) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2022.3180274 · Cited by 160 · see citing works
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Zhang, W., Ji, G.-P., Wang, Z., Fu, K., & Zhao, Q. (2021) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3474085.3475240 · Cited by 160 · see citing works
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Huo, F., Zhu, X., Zhang, Q., Liu, Z., & Yu, W. (2022) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2022.3185323 · Cited by 156 · see citing works
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Wang, F., Pan, J., Xu, S., & Tang, J. (2022) · IEEE Transactions on Image Processing · doi:10.1109/tip.2022.3140606 · Cited by 152 · see citing works
HRTransNet: HRFormer-Driven Two-Modality Salient Object Detection
Tang, B., Liu, Z., Tan, Y., & He, Q. (2022) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2022.3202563 · Cited by 149 · see citing works
Source-free Depth for Object Pop-out
Wu, Z., Paudel, D. P., Fan, D.-P., Wang, J., Wang, S., Demonceaux, C., Timofte, R., & Gool, L. V. (2023) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv51070.2023.00101 · Cited by 148 · see citing works
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Fan, D.-P., Li, T., Zheng, L. L., Ji, G.-P., Zhang, D., Cheng, M., Fu, H., & Shen, J. (2021) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2021.3060412 · Cited by 144 · see citing works
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Zhang, J., Fan, D.-P., Dai, Y., Anwar, S., Saleh, F. S., Aliakbarian, S., & Barnes, N. M. (2021) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2021.3073564 · Cited by 142 · see citing works
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Cong, R., Zhang, K., Zhang, C. G., Zheng, F., Zhao, Y., Huang, Q., & Kwong, S. (2022) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2022.3216476 · Cited by 134 · see citing works
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Fan, D.-P., Ji, G.-P., Xu, P., Cheng, M., Sakaridis, C., & Gool, L. V. (2023) · Visual Intelligence · doi:10.1007/s44267-023-00019-6 · Cited by 137 · see citing works
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Chen, T., Xiao, J., Hu, X., Zhang, G., & Wang, S. (2022) · Knowledge-Based Systems · doi:10.1016/j.knosys.2022.108901 · Cited by 129 · see citing works
Learning Selective Mutual Attention and Contrast for RGB-D Saliency Detection
Liu, N., Zhang, N., Shao, L., & Han, J. (2021) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2021.3122139 · Cited by 122 · see citing works
Self-citationZoomNeXt: A Unified Collaborative Pyramid Network for Camouflaged Object Detection
Pang, Y., Zhao, X., Xiang, T.-Z., Zhang, L., & Lu, H. (2024) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2024.3417329 · Cited by 128 · see citing works
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Zhang, Y., Zhang, T., Wu, C., & Tao, R. (2023) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2023.3321394 · Cited by 121 · see citing works
USOD10K: A New Benchmark Dataset for Underwater Salient Object Detection
Hong, L., Wang, X., Zhang, G., & Zhao, M. L. (2023) · IEEE Transactions on Image Processing · doi:10.1109/tip.2023.3266163 · Cited by 121 · see citing works
Group Collaborative Learning for Co-Salient Object Detection
Fan, Q., Fan, D.-P., Fu, H., Tang, C., Shao, L., & Tai, Y. (2021) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr46437.2021.01211 · Cited by 114 · see citing works
Self-citationCross-modal hierarchical interaction network for RGB-D salient object detection
Bi, H., Wu, R., Liu, Z., Zhu, H., Zhang, C., & Xiang, T.-Z. (2022) · Pattern Recognition · doi:10.1016/j.patcog.2022.109194 · Cited by 113 · see citing works
BTS-Net: Bi-Directional Transfer-And-Selection Network for RGB-D Salient Object Detection
Zhang, W., Jiang, Y., Fu, K., & Zhao, Q. (2021) · IEEE International Conference on Multimedia and Expo (ICME) · doi:10.1109/icme51207.2021.9428263 · Cited by 110 · see citing works
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Chen, C., Wei, J., Peng, C., & Qin, H. (2021) · IEEE Transactions on Image Processing · doi:10.1109/tip.2021.3052069 · Cited by 109 · see citing works
Song, K., Huang, L., Gong, A., & Yan, Y. (2022) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2022.3233131 · Cited by 109 · see citing works
SC-DepthV3: Robust Self-Supervised Monocular Depth Estimation for Dynamic Scenes
Sun, L., Bian, J.-W., Zhan, H., Yin, W., Reid, I. D., & Shen, C. (2023) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2023.3322549 · Cited by 108 · see citing works
Cross-Collaborative Fusion-Encoder Network for Robust RGB-Thermal Salient Object Detection
Liao, G., Gao, W., Li, G., Wang, J., & Kwong, S. (2022) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2022.3184840 · Cited by 103 · see citing works
FCMNet: Frequency-aware cross-modality attention networks for RGB-D salient object detection
Jin, X. H., Guo, C., He, Z., Xu, J., Wang, Y., & Su, Y. (2022) · Neurocomputing · doi:10.1016/j.neucom.2022.04.015 · Cited by 105 · see citing works
LPViT: A Transformer Based Model for PCB Image Classification and Defect Detection
An, K., & Zhang, Y. (2022) · IEEE Access · doi:10.1109/access.2022.3168861 · Cited by 103 · see citing works
3-D Convolutional Neural Networks for RGB-D Salient Object Detection and Beyond
Chen, Q., Zhang, Z., Lu, Y., Fu, K., & Zhao, Q. (2022) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2022.3202241 · Cited by 99 · see citing works
Modality-Induced Transfer-Fusion Network for RGB-D and RGB-T Salient Object Detection
Chen, G., Shao, F., Chai, X., Chen, H., Jiang, Q., Meng, X., & Ho, Y. (2022) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2022.3215979 · Cited by 99 · see citing works
Salient Object Detection Techniques in Computer Vision—A Survey
Gupta, A. K., Seal, A., Prasad, M., & Khanna, P. (2020) · Entropy · doi:10.3390/e22101174 · Cited by 99 · see citing works
Data-Level Recombination and Lightweight Fusion Scheme for RGB-D Salient Object Detection
Wang, X., Li, S., Chen, C., Fang, Y., Hao, A., & Qin, H. (2020) · IEEE Transactions on Image Processing · doi:10.1109/tip.2020.3037470 · Cited by 91 · see citing works
Light field salient object detection: A review and benchmark
Fu, K., Jiang, Y., Ji, G.-P., Zhou, T., Zhao, Q., & Fan, D.-P. (2022) · Computational Visual Media · doi:10.1007/s41095-021-0256-2 · Cited by 90 · see citing works
Self-citationHuang, Z., Chen, H., Liu, B., & Wang, Z. (2021) · Remote Sensing · doi:10.3390/rs13112163 · Cited by 90 · see citing works
Multispectral Object Detection via Cross-Modal Conflict-Aware Learning
He, X., Tang, C., Zou, X. G., & Zhang, W. (2023) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3581783.3612651 · Cited by 89 · see citing works
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Cong, R., Liu, H., Zhang, C., Zhang, W., Zheng, F., Song, R., & Kwong, S. (2023) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3581783.3611982 · Cited by 82 · see citing works
Transformer Fusion and Pixel-Level Contrastive Learning for RGB-D Salient Object Detection
Wu, J., Hao, F., Liang, W., & Xu, J. (2023) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2023.3275308 · Cited by 80 · see citing works
DMRA: Depth-Induced Multi-Scale Recurrent Attention Network for RGB-D Saliency Detection
Ji, W., Yan, G., Li, J., Piao, Y., Yao, S., Zhang, M., Cheng, L., & Lu, H. (2022) · IEEE Transactions on Image Processing · doi:10.1109/tip.2022.3154931 · Cited by 77 · see citing works
Wei, S., Luo, C., & Luo, Y. (2023) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52729.2023.01919 · Cited by 75 · see citing works
Uncertainty-Aware Hierarchical Aggregation Network for Medical Image Segmentation
Zhou, T., Zhou, Y., Li, G., Chen, G., & Shen, J. (2024) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2024.3370685 · Cited by 74 · see citing works
Self-citationA systematic review of object detection from images using deep learning
Kaur, J., & Singh, W. (2023) · Multimedia Tools and Applications · doi:10.1007/s11042-023-15981-y · Cited by 75 · see citing works
Fan, D.-P., Zhang, J., Xu, G., Cheng, M., & Shao, L. (2022) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2022.3166451 · Cited by 70 · see citing works
Self-citationXu, Y., Yu, X., Zhang, J., Zhu, L., & Wang, D. (2022) · IEEE Transactions on Image Processing · doi:10.1109/tip.2022.3151999 · Cited by 65 · see citing works
Light Field Saliency Detection with Dual Local Graph Learning and Reciprocative Guidance
Liu, N., Zhao, W., Zhang, D., Han, J., & Shao, L. (2021) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv48922.2021.00467 · Cited by 63 · see citing works
Self-citationEF-Net: A novel enhancement and fusion network for RGB-D saliency detection
Chen, Q., Fu, K., Liu, Z., Chen, G., Du, H., Qiu, B., & Shao, L. (2020) · Pattern Recognition · doi:10.1016/j.patcog.2020.107740 · Cited by 62 · see citing works
Self-citationMiddle-Level Feature Fusion for Lightweight RGB-D Salient Object Detection
Huang, N., Jiao, Q., Zhang, Q., & Han, J. (2022) · IEEE Transactions on Image Processing · doi:10.1109/tip.2022.3214092 · Cited by 61 · see citing works
Wang, H., Song, K., Huang, L., Wen, H., & Yan, Y. (2022) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2022.105640 · Cited by 60 · see citing works
VST++: Efficient and Stronger Visual Saliency Transformer
Liu, N., Luo, Z., Zhang, N., & Han, J. (2024) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2024.3388153 · Cited by 60 · see citing works
Zhou, M., Cheng, W., Huang, H., & Chen, J. (2021) · Sensors · doi:10.3390/s21175725 · Cited by 59 · see citing works
Robust RGB-D Fusion for Saliency Detection
Wu, Z., Gobichettipalayam, S., Tamadazte, B., Allibert, G., Paudel, D. P., & Demonceaux, C. (2022) · International Conference on 3D Vision (3DV) · doi:10.1109/3dv57658.2022.00052 · Cited by 58 · see citing works
EM-Trans: Edge-Aware Multimodal Transformer for RGB-D Salient Object Detection
Chen, G., Wang, Q., Dong, B., Ma, R., Liu, N., Fu, H., & Xia, Y. (2024) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2024.3358858 · Cited by 59 · see citing works
Xu, K., Shu, L., Xie, Q., Song, M., Zhu, Y. Q., Cao, W., & Ni, J. (2023) · Computers and Electronics in Agriculture · doi:10.1016/j.compag.2023.108106 · Cited by 57 · see citing works
RGB-D Salient Object Detection With Ubiquitous Target Awareness
Zhao, Y., Zhao, J., Li, J., & Chen, X. (2021) · IEEE Transactions on Image Processing · doi:10.1109/tip.2021.3108412 · Cited by 55 · see citing works
GAN-based generation of realistic 3D volumetric data: A systematic review and taxonomy
Ferreira, A. F., Li, J., Pomykala, K. L., Kleesiek, J., Alves, V., & Egger, J. (2024) · Medical Image Analysis · doi:10.1016/j.media.2024.103100 · Cited by 63 · see citing works
Huang, Z., Xiang, T.-Z., Chen, H., & Dai, H. (2022) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2022.07.014 · Cited by 54 · see citing works
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Fan, S., Gao, W., & Li, G. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-19815-1_1 · Cited by 53 · see citing works
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Li, L., Han, J., Liu, N., Khan, S. H., Cholakkal, H., Anwer, R. M., & Khan, F. S. (2023) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2023.3324807 · Cited by 53 · see citing works
Wang, K., Lin, D., Li, C., Tu, Z., & Luo, B. (2024) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2024.3410542 · Cited by 53 · see citing works
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Zhang, N., Han, J., & Liu, N. (2022) · IEEE Transactions on Image Processing · doi:10.1109/tip.2022.3185550 · Cited by 50 · see citing works
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Liu, J., Liu, Z., Peng, P., & Cheng, M. (2021) · IEEE Transactions on Image Processing · doi:10.1109/tip.2021.3122093 · Cited by 50 · see citing works
Self-citationM 2 RNet: Multi-modal and multi-scale refined network for RGB-D salient object detection
Fang, X., Jiang, M., Zhu, J., Shao, X., & Wang, H. (2022) · Pattern Recognition · doi:10.1016/j.patcog.2022.109139 · Cited by 47 · see citing works
Rodríguez, I., Campos, C., & Fdez‐Riverola, F. (2021) · Neural Computing and Applications · doi:10.1007/s00521-021-06830-w · Cited by 49 · see citing works
ELWNet: An Extremely Lightweight Approach for Real-Time Salient Object Detection
Wang, Z., Zhang, Y., Liu, Y., Zhu, D., Coleman, S., & Kerr, D. (2023) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2023.3269951 · Cited by 45 · see citing works
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Rezaei, M., Azarmi, M., & Mir, F. M. P. (2023) · Expert Systems with Applications · doi:10.1016/j.eswa.2023.120253 · Cited by 45 · see citing works
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Liang, Y., Qin, G., Sun, M., Wang, X., Yan, J., & Zhang, Z. (2023) · Neurocomputing · doi:10.1016/j.neucom.2023.127050 · Cited by 45 · see citing works
RLLNet: a lightweight remaking learning network for saliency redetection on RGB-D images
Zhou, W., Liu, C., Lei, J., & Yu, L. (2022) · Science China Information Sciences · doi:10.1007/s11432-020-3337-9 · Cited by 43 · see citing works
DCMNet: Discriminant and cross-modality network for RGB-D salient object detection
Wang, F., Wang, R., & Sun, F. (2022) · Expert Systems with Applications · doi:10.1016/j.eswa.2022.119047 · Cited by 42 · see citing works
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Jiang, X., Hou, Y., Tian, H., & Zhu, L. (2023) · IET Computer Vision · doi:10.1049/cvi2.12221 · Cited by 42 · see citing works
Marques, T., Carreira, S., Miragaia, R., Ramos, J., & Pereira, A. M. D. J. (2024) · Expert Systems with Applications · doi:10.1016/j.eswa.2023.123107 · Cited by 45 · see citing works
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Huang, Y., Xu, S., Chen, H., Li, G., Dong, H., Yu, J., Zhang, X., & Chen, R. (2025) · Frontiers in Plant Science · doi:10.3389/fpls.2025.1646871 · Cited by 41 · see citing works
Li, Y., Liu, G., Bavirisetti, D. P., Gu, X., & Zhou, X. (2023) · Digital Signal Processing · doi:10.1016/j.dsp.2023.103910 · Cited by 40 · see citing works
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Liu, X., Qi, L., Song, Y., & Wen, Q. (2024) · Image and Vision Computing · doi:10.1016/j.imavis.2024.104924 · Cited by 39 · see citing works
Chen, Y., Li, G., An, P., Liu, Z., Huang, X., & Wu, Q. (2023) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2023.3290600 · Cited by 38 · see citing works
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Feng, G., Meng, J., Zhang, L., & Lu, H. (2022) · Pattern Recognition · doi:10.1016/j.patcog.2022.108666 · Cited by 38 · see citing works
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Zhou, T., Zhang, Y., Chen, G., Zhou, Y., Wu, Y., & Fan, D.-P. (2023) · Machine Intelligence Research · doi:10.1007/s11633-023-1479-8 · Cited by 39 · see citing works
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Huang, Z., Chen, H., Zhou, T., Yun-zhi, Y., & Liu, B. (2021) · Neurocomputing · doi:10.1016/j.neucom.2021.04.053 · Cited by 37 · see citing works
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Wang, R., Wang, F., Su, Y., Sun, J., Sun, F., & Li, H. (2023) · ACM Transactions on Multimedia Computing Communications and Applications · doi:10.1145/3624747 · Cited by 34 · see citing works
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Xu, C. X., Li, Q., Zhou, Q., Jiang, X., Yu, D., & Zhou, Y. (2022) · Knowledge-Based Systems · doi:10.1016/j.knosys.2022.110047 · Cited by 34 · see citing works
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Li, L., Rigall, E., Dong, J., & Chen, G. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-71058-3_12 · Cited by 33 · see citing works
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Chen, G., Fu, H., Zhou, T., Xiao, G., Fu, K., Xia, Y., & Zhang, Y. (2023) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2023.3274933 · Cited by 33 · see citing works
Self-citation
- Authors
- Zhou, T., Fan, D.-P., Cheng, M.-M., Shen, J., & Shao, L.
- Affiliations
- Inception Institute of Artificial Intelligence (AE)
- Nankai University (CN)
- Corresponding author
- Fan, Deng-Ping
- Venue
- Computational Visual Media
- Publisher
- Tsinghua University Press
- Published
- 2021-03
- Volume
- 7
- Issue
- 1
- Pages
- 37-69
- ISSN
- 2096-0433 (ISSN-L)
- 2096-0662
- PMC
- PMC7788385
- OpenAlex
- W3046597754
- Cited by
- 331
- References
- 227
- Citations by year
- 2026: 33 · 2025: 42 · 2024: 50 · 2023: 70 · 2022: 76 · 2021: 50 · 2020: 9 · 2019: 1
- FWCI
- 3.76
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Locations
- Computational Visual Media (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Funders
- National Natural Science Foundation of China (61922046, 2018AAA0100400)
- Natural Science Foundation of Tianjin City (17JCJQJC43700)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Visual Attention and Saliency Detection
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Neural Network Applications
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Vision and Imaging
- Keywords
- salient object detection, RGB-D, depth images, light field, benchmark dataset, visual perception, depth sensors
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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