Scale-Aware Face Detection

Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

Ren, S., He, K., Girshick, R., & Sun, J. (2015) · arXiv · doi:10.48550/arxiv.1506.01497 · Cited by 70,812 · see citing works

Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

Ren, S., He, K., Girshick, R., & Sun, J. (2017) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2016.2577031 · Cited by 56,035 · see citing works

You Only Look Once: Unified, Real-Time Object Detection

Redmon, J., Divvala, S., Girshick, R., & Farhadi, A. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.91 · Cited by 53,803 · see citing works

Microsoft COCO: Common Objects in Context

Lin, T.-Y., Maire, M., Belongie, S., Hays, J., Perona, P., Ramanan, D., Dollár, P., & Zitnick, C. L. (2014) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-10602-1_48 · Cited by 45,460 · see citing works

Histograms of Oriented Gradients for Human Detection

Dalal, N., & Triggs, B. (2005) · 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) · doi:10.1109/cvpr.2005.177 · Cited by 33,584 · see citing works

Untitled work

(2016) · Cited by 31,590 · see citing works

Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

Ioffe, S., & Szegedy, C. (2015) · arXiv · doi:10.48550/arxiv.1502.03167 · Cited by 27,818 · see citing works

Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate ShiftPreprint

Ioffe, S. (2024) · arXiv (Cornell University) · doi:10.57702/o9raffed · Cited by 15,273 · see citing works

Robust Real-Time Face Detection

Viola, P., & Jones, M. J. (2004) · International Journal of Computer Vision · doi:10.1023/b:visi.0000013087.49260.fb · Cited by 14,097 · see citing works

Object Detection with Discriminatively Trained Part-Based Models

Felzenszwalb, P. F., Girshick, R. B., McAllester, D., & Ramanan, D. (2010) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2009.167 · Cited by 9,853 · see citing works

R-FCN: Object Detection via Region-based Fully Convolutional NetworksPreprint

Dai, J., Li, Y., He, K., & Sun, J. Z. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1605.06409 · Cited by 5,135 · see citing works

Neural network-based face detection

Rowley, H. A., Baluja, S., & Kanade, T. (1998) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.655647 · Cited by 3,554 · see citing works

Face detection, pose estimation, and landmark localization in the wild

Zhu, X., & Ramanan, D. (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.2012.6248014 · Cited by 2,171 · see citing works

Fast Feature Pyramids for Object Detection

Dollár, P., Appel, R., Belongie, S., & Perona, P. (2014) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2014.2300479 · Cited by 1,941 · see citing works

A Unified Multi-scale Deep Convolutional Neural Network for Fast Object Detection

Cai, Z., Fan, Q., Feris, R. S., & Vasconcelos, N. (2016) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-46493-0_22 · Cited by 1,605 · see citing works

A convolutional neural network cascade for face detection

Li, H., Lin, Z., Shen, X., Brandt, J., & Hua, G. (2015) · 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2015.7299170 · Cited by 1,390 · see citing works

Inside-Outside Net: Detecting Objects in Context with Skip Pooling and Recurrent Neural Networks

Bell, S., Zitnick, C. L., Bala, K., & Girshick, R. (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.2016.314 · Cited by 1,344 · see citing works

Annotated Facial Landmarks in the Wild: A large-scale, real-world database for facial landmark localization

Köstinger, M., Wohlhart, P., Roth, P. M., & Bischof, H. (2011) · IEEE International Conference on Computer Vision Workshops · doi:10.1109/iccvw.2011.6130513 · Cited by 1,004 · see citing works

FDDB: A benchmark for face detection in unconstrained settings

Jain, V., & Miller, E. G. (2010) · ScholarWorks@UMassAmherst (University of Massachusetts Amherst) · Cited by 879 · see citing works

Multiple Instance Boosting for Object Detection

Zhang, C., Platt, J. C., & Viola, P. A. (2005) · neural information processing systems · Cited by 692 · see citing works

Fast Multi-view Face Detection

Jones, M., & Viola, P. A. (2003) · CTIT technical reports series · Cited by 615 · see citing works

Multi-view Face Detection Using Deep Convolutional Neural Networks

Farfade, S., Saberian, M. J., & Li, L.-J. (2015) · International Conference on Multimedia Retrieval · doi:10.1145/2671188.2749408 · Cited by 583 · see citing works

From Facial Parts Responses to Face Detection: A Deep Learning Approach

Yang, S., Luo, P., Loy, C. C., & Tang, X. (2015) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2015.419 · Cited by 574 · see citing works

FloatBoost learning and statistical face detection

Li, S. Z., & Zhang, Z. (2004) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2004.68 · Cited by 525 · see citing works

Face Detection without Bells and Whistles

Mathias, M., Benenson, R., Pedersoli, M., & Gool, L. V. (2014) · Lecture notes in computer science · doi:10.1007/978-3-319-10593-2_47 · Cited by 505 · see citing works

Rotation Invariant Neural Network-Based Face Detection

Rowley, H. A., Baluja, S., & Takeo Kanade, A. (2005) · 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.1998.698721 · Cited by 470 · see citing works

Face Detection Based on Multi-Block LBP Representation

Zhang, L., Chu, R.-F., Xiang, S., Liao, S.-C., & Li, S. (2007) · International Conference on Biometrics · doi:10.1007/978-3-540-74549-5_2 · Cited by 448 · see citing works

DenseBox: Unifying Landmark Localization with End to End Object Detection

Huang, L., Yang, Y., Deng, Y., & Yu, Y. (2015) · arXiv · doi:10.48550/arxiv.1509.04874 · Cited by 407 · see citing works

Statistical Learning of Multi-view Face Detection

Li, S. Z., Zhu, L., Zhang, Z., Blake, A., Zhang, H., & Shum, H. (2002) · Lecture notes in computer science · doi:10.1007/3-540-47979-1_5 · Cited by 404 · see citing works

High-Performance Rotation Invariant Multiview Face Detection

Huang, C., Ai, H., Li, Y., & Lao, S. (2007) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2007.1011 · Cited by 388 · see citing works

Robust Object Detection via Soft Cascade

Bourdev, L., & Brandt, J. (2005) · 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.2005.310 · Cited by 329 · see citing works

The Fastest Deformable Part Model for Object Detection

Yan, J., Lei, Z., Wen, L., & Li, S. Z. (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.2014.320 · Cited by 287 · see citing works

Aggregate channel features for multi-view face detection

Yang, B., Yan, J., Lei, Z., & Li, S. Z. (2014) · IEEE International Joint Conference on Biometrics (IJCB) · doi:10.1109/btas.2014.6996284 · Cited by 286 · see citing works

Original approach for the localisation of objects in images

Vaillant, R. (1994) · IEE Proceedings - Vision, Image, and Signal Processing · doi:10.1049/ip-vis:19941301 · Cited by 280 · see citing works

Vector boosting for rotation invariant multi-view face detection

Huang, C., Ai, H., Li, Y., & Lao, S. (2005) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2005.246 · Cited by 216 · see citing works

Joint Training of Cascaded CNN for Face Detection

Qin, H., Yan, J., Li, X., & Hu, X. (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.2016.376 · Cited by 216 · see citing works

Learning SURF Cascade for Fast and Accurate Object Detection

Li, J., & Zhang, Y. (2013) · 2013 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2013.445 · Cited by 213 · see citing works

Supervised Transformer Network for Efficient Face Detection

Chen, D., Hua, G., Wen, F., & Sun, J. (2016) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-46454-1_8 · Cited by 185 · see citing works

A deep pyramid Deformable Part Model for face detection

Ranjan, R., Patel, V. M., & Chellappa, R. (2015) · IEEE International Conference on Biometrics: Theory, Applications and Systems (BTAS) · doi:10.1109/btas.2015.7358755 · Cited by 153 · see citing works

Rotation invariant neural network-based face detection

Rowley, H. A., Baluja, S., & Takeo Kanade, A. (2002) · 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.1998.698585 · Cited by 131 · see citing works

Fine-grained evaluation on face detection in the wild

Yang, B., Yan, J., Lei, Z., & Li, S. Z. (2015) · International Conference on Automatic Face and Gesture Recognition · doi:10.1109/fg.2015.7163158 · Cited by 68 · see citing works

Occlusion Coherence: Detecting and Localizing Occluded FacesPreprint

Ghiasi, G., & Fowlkes, C. C. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1506.08347 · Cited by 58 · see citing works

Convolutional Channel Features For Pedestrian, Face and Edge Detection.Preprint

Yang, B., Yan, J., Lei, Z., & Li, S. Z. (2015) · arXiv (Cornell University) · Cited by 15 · 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

Object Detection in 20 Years: A Survey

Zou, Z., Chen, K., Shi, Z., Guo, Y., & Ye, J. (2023) · Proceedings of the IEEE · doi:10.1109/jproc.2023.3238524 · Cited by 3,689 · see citing works

Recent advances in deep learning for object detection

Wu, X., Sahoo, D., & Hoi, S. C. H. (2020) · Neurocomputing · doi:10.1016/j.neucom.2020.01.085 · Cited by 1,047 · see citing works

Dynamic Neural Networks: A Survey

Han, Y., Huang, G., Song, S., Yang, L., Wang, H., & Wang, Y. (2022) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2021.3117837 · Cited by 848 · see citing works

FSRNet: End-to-End Learning Face Super-Resolution with Facial Priors

Chen, Y., Tai, Y. Y., Liu, X., Shen, C., & Yang, J. 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.2018.00264 · Cited by 600 · see citing works

A review of object detection based on deep learning

Xiao, Y., Tian, Z., Yu, J., Zhang, Y., Liu, S., Du, S., & Lan, X. (2020) · Multimedia Tools and Applications · doi:10.1007/s11042-020-08976-6 · Cited by 584 · see citing works

RetinaFace: Single-stage Dense Face Localisation in the WildPreprint

Deng, J., Guo, J., Zhou, Y., Yu, J., Kotsia, I., & Zafeiriou, S. P. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1905.00641 · Cited by 518 · see citing works

Revisiting the Sibling Head in Object Detector

Song, G., Liu, Y., & Wang, X. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr42600.2020.01158 · Cited by 509 · see citing works

Image-Based Surface Defect Detection Using Deep Learning: A Review

Bhatt, P. M., Malhan, R. K., Rajendran, P. S., Shah, B. C., Thakar, S., Yoon, Y. J., & Gupta, S. K. (2021) · Journal of Computing and Information Science in Engineering · doi:10.1115/1.4049535 · Cited by 380 · see citing works

Selective Refinement Network for High Performance Face Detection

Chi, C., Zhang, S., Xing, J., Lei, Z., Li, S. Z., & Zou, X. (2019) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v33i01.33018231 · Cited by 177 · see citing works

Investigations of Object Detection in Images/Videos Using Various Deep Learning Techniques and Embedded Platforms—A Comprehensive Review

Chintakindi, B. M., Hashmi, M. F., Bokde, N. D., & Geem, Z. W. (2020) · Applied Sciences · doi:10.3390/app10093280 · Cited by 177 · see citing works

The Elements of End-to-end Deep Face Recognition: A Survey of Recent Advances

Du, H., Shi, H., Zeng, D., Zhang, X.-P. S., & Mei, T. (2022) · ACM Computing Surveys · doi:10.1145/3507902 · Cited by 163 · see citing works

Dual-Path Deep Fusion Network for Face Image Hallucination

Jiang, K., Wang, Z., Yi, P., Lu, T., Jiang, J., & Xiong, Z. (2020) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2020.3027849 · Cited by 142 · see citing works

MSR: Multi-Scale Shape Regression for Scene Text Detection

Xue, C., Lu, S., & Zhang, W. (2019) · International Joint Conference on Artificial Intelligence · doi:10.24963/ijcai.2019/139 · Cited by 141 · see citing works

Face Attention Network: An Effective Face Detector for the Occluded FacesPreprint

Wang, J., Yuan, Y., & Yu, G. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1711.07246 · Cited by 131 · see citing works

ATMFN: Adaptive-Threshold-Based Multi-Model Fusion Network for Compressed Face Hallucination

Jiang, K., Wang, Z., Yi, P., Wang, G., Gu, K., & Jiang, J. (2019) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2019.2960586 · Cited by 129 · see citing works

Feature agglomeration networks for single stage face detection

Zhang, J., Wu, X., Hoi, S. C. H., & Zhu, J. (2019) · Neurocomputing · doi:10.1016/j.neucom.2019.10.087 · Cited by 128 · see citing works

RefineFace: Refinement Neural Network for High Performance Face Detection

Zhang, S., Chi, C., Lei, Z., & Li, S. Z. (2020) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2020.2997456 · Cited by 113 · see citing works

Recurrent Scale Approximation for Object Detection in CNN

Liu, Y., Li, H., Yan, J., Wei, F., Wang, X., & Tang, X. (2017) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2017.69 · Cited by 92 · see citing works

DualSDF: Semantic Shape Manipulation Using a Two-Level Representation

Hao, Z., Averbuch‐Elor, H., Snavely, N., & Belongie, 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/cvpr42600.2020.00765 · Cited by 92 · see citing works

High-Level Semantic Networks for Multi-Scale Object Detection

Cao, J., Pang, Y., Zhao, S., & Li, X. (2019) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2019.2950526 · Cited by 87 · see citing works

Recurrent Exposure Generation for Low-Light Face Detection

Liang, J., Wang, J., Quan, Y., Chen, T., Liu, J., Ling, H., & Xu, Y. (2021) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2021.3068840 · Cited by 86 · see citing works

Deep learning-based small object detection: A survey

Feng, Q., Xu, X., & Wang, Z. (2023) · Mathematical Biosciences & Engineering · doi:10.3934/mbe.2023282 · Cited by 97 · see citing works

A fast face detection method via convolutional neural network

Guo, G., Wang, H., Yan, Y., Zheng, J. Y., & Li, B. H. (2019) · Neurocomputing · doi:10.1016/j.neucom.2018.02.110 · Cited by 76 · see citing works

Multiscale Deep Learning for Detection and Recognition: A Comprehensive Survey

Jiao, L., Wang, M., Liu, X., Li, L., Liu, F., Feng, Z., Yang, S., & Hou, B. (2024) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2024.3389454 · Cited by 76 · see citing works

A 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

HAMBox: Delving Into Mining High-Quality Anchors on Face Detection

Liu, Y., Tang, X., Han, J., Liu, J., Rui, D., & Wu, X. (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/cvpr42600.2020.01306 · Cited by 61 · see citing works

Face Detection Using Improved Faster RCNNPreprint

Zhang, C., Xu, X., & Tu, D. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1802.02142 · Cited by 60 · see citing works

Deep Learning for Object Detection: A Survey

Wang, J., Zhang, T., Cheng, Y. J., & Al-Nabhan, N. (2021) · Computer Systems Science and Engineering · doi:10.32604/csse.2021.017016 · Cited by 59 · see citing works

Detect Faces Efficiently: A Survey and Evaluations

Feng, Y., Yu, S., Peng, H., Li, Y.-R., & Zhang, J. (2022) · IEEE Transactions on Biometrics Behavior and Identity Science · doi:10.1109/tbiom.2021.3120412 · Cited by 55 · see citing works

Faceboxes: A CPU real-time and accurate unconstrained face detector

Zhang, S., Wang, X., Lei, Z., & Li, S. Z. (2019) · Neurocomputing · doi:10.1016/j.neucom.2019.07.064 · Cited by 53 · see citing works

Realtime multi-scale scene text detection with scale-based region proposal network

He, W., Zhang, X.-Y., Yin, F., Luo, Z., Ogier, J.-M., & Liu, C. (2019) · Pattern Recognition · doi:10.1016/j.patcog.2019.107026 · Cited by 51 · see citing works

Registration-free Face-SSD: Single shot analysis of smiles, facial attributes, and affect in the wild

Jang, Y., Güneş, H., & Patras, I. (2019) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2019.01.006 · Cited by 51 · see citing works

HeadNet: An End-to-End Adaptive Relational Network for Head Detection

Li, W., Li, H., Wu, Q., Meng, F., Xu, L., & Ngan, K. N. (2019) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2019.2890840 · Cited by 49 · see citing works

Efficient face detection and tracking in video sequences based on deep learning

Zheng, G., & Xu, Y. (2021) · Information Sciences · doi:10.1016/j.ins.2021.03.027 · Cited by 42 · see citing works

Simultaneous Face Detection and Pose Estimation Using Convolutional Neural Network Cascade

Wu, H., Zhang, K., & Tian, G. (2018) · IEEE Access · doi:10.1109/access.2018.2869465 · Cited by 39 · see citing works

Anchor Cascade for Efficient Face Detection

Yu, B., & Tao, D. (2018) · IEEE Transactions on Image Processing · doi:10.1109/tip.2018.2886790 · Cited by 38 · see citing works

Beyond Trade-Off: Accelerate FCN-Based Face Detector with Higher Accuracy

Song, G., Liu, Y., Jiang, M., Wang, Y., Yan, J., & Leng, B. (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.2018.00809 · Cited by 38 · see citing works

Facial Landmark Machines: A Backbone-Branches Architecture With Progressive Representation Learning

Liu, L., Li, G., Xie, Y., Yu, Y., Wang, Q., & Lin, L. (2019) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2019.2902096 · Cited by 35 · see citing works

A Deep-Fusion Network for Crowd Counting in High-Density Crowded Scenes

Khan, S. D., Salih, Y., Zafar, B., & Noorwali, A. (2021) · International Journal of Computational Intelligence Systems · doi:10.1007/s44196-021-00016-x · Cited by 34 · see citing works

FastPose: Towards Real-time Pose Estimation and Tracking via Scale-normalized Multi-task NetworksPreprint

Zhang, J., Zhu, Z. D., Zou, W., Li, P., Li, Y., Su, H., & Huang, G. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1908.05593 · Cited by 34 · see citing works

Hierarchical Attention for Part-Aware Face Detection

Wu, S., Kan, M.-N., Shan, S., & Chen, X.-L. (2019) · International Journal of Computer Vision · doi:10.1007/s11263-019-01157-5 · Cited by 31 · see citing works

The Role of Deep Learning in Manufacturing Applications: Challenges and Opportunities

Malhan, R. K., & Gupta, S. K. (2023) · Journal of Computing and Information Science in Engineering · doi:10.1115/1.4062939 · Cited by 32 · see citing works

SurfConv: Bridging 3D and 2D Convolution for RGBD Images

Chu, H., Ma, W.-C., Kundu, K., Urtasun, R., & Fidler, S. (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.2018.00317 · Cited by 30 · see citing works

Improved Selective Refinement Network for Face DetectionPreprint

Zhang, S., Zhu, R., Wang, X., Shi, H., Fu, T., Wang, S., Mei, T., & Li, S. Z. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1901.06651 · Cited by 34 · see citing works

Fast face detection on mobile devices by leveraging global and local facial characteristics

Zhang, H., Wang, X., Zhu, J., & Kuo, C. ‐. J. (2019) · Signal Processing Image Communication · doi:10.1016/j.image.2019.05.016 · Cited by 29 · see citing works

Resolution Learning in Deep Convolutional Networks Using Scale-Space Theory

Pintea, S. L., Tömen, N., Goes, S. F., Loog, M., & van Gemert, J. C. (2021) · IEEE Transactions on Image Processing · doi:10.1109/tip.2021.3115001 · Cited by 29 · see citing works

Scale-Aware Hierarchical Detection Network for Pedestrian Detection

Zhang, X., Cao, S., & Chen, C. (2020) · IEEE Access · doi:10.1109/access.2020.2995321 · Cited by 28 · see citing works

A Deep Learning Approach to Driver Distraction Detection of Using Mobile Phone

Xiong, Q., Lin, J. T., Wei, Y., Liu, S., Liu, Y., & Ding, C. (2019) · IEEE Vehicle Power and Propulsion Conference (VPPC) · doi:10.1109/vppc46532.2019.8952474 · Cited by 27 · see citing works

Robust Haze and Thin Cloud Removal via Conditional Variational Autoencoders

Ding, H., Xie, F., Qiu, L., Zhang, X., & Shi, Z. (2024) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2024.3349779 · Cited by 26 · see citing works

Deep Kinship Verification VIA Appearance-Shape Joint Prediction and Adaptation-Based Approach

Zhang, H., Wang, X., & Kuo, C. ‐. J. (2019) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2019.8803647 · Cited by 24 · see citing works

Similar Face Recognition Using the IE-CNN Model

Song, A., Hu, Q., Ding, X., Di, X., & Song, Z.-H. (2020) · IEEE Access · doi:10.1109/access.2020.2978938 · Cited by 24 · see citing works

Accurate Face Detection for High PerformancePreprint

Zhang, F., Fan, X., Ai, G., Song, J., Qin, Y., & Wu, J. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1905.01585 · Cited by 23 · see citing works

Neural network developments: A detailed survey from static to dynamic models

Verma, P. R., Singh, N. P., Pantola, D., & Cheng, X. (2024) · Computers & Electrical Engineering · doi:10.1016/j.compeleceng.2024.109710 · Cited by 25 · see citing works

A Fine-Grained Semantic Alignment Method Specific to Aggregate Multi-Scale Information for Cross-Modal Remote Sensing Image Retrieval

Zheng, F., Wang, X., Wang, L., Zhang, X., Zhu, H., Wang, L., & Zhang, H. (2023) · Sensors · doi:10.3390/s23208437 · Cited by 21 · see citing works

iQIYI-VID: A Large Dataset for Multi-modal Person IdentificationPreprint

Liu, Y., Peng, B., Shi, P., Yan, H., Zhou, Y., Han, B., Zheng, Y., Lin, C., Jiang, J., Yin, F., et al. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1811.07548 · Cited by 35 · see citing works

Robust and High Performance Face DetectorPreprint

Zhang, Y., Xu, X., & Liu, X. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1901.02350 · Cited by 21 · see citing works

Multi-Scale, Class-Generic, Privacy-Preserving Video

Zhang, Z., Cilloni, T., Walter, C., & Fleming, C. (2021) · Electronics · doi:10.3390/electronics10101172 · Cited by 20 · see citing works

Joint Learning of Blind Super-Resolution and Crack Segmentation for Realistic Degraded Images

Kondo, Y., & Ukita, N. (2024) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2024.3374293 · Cited by 22 · see citing works

SFace: An Efficient Network for Face Detection in Large Scale VariationsPreprint

Wang, J., Yuan, Y., Li, B., Yu, G., & Sun, J. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1804.06559 · Cited by 20 · see citing works

Keep an eye on faces: Robust face detection with heatmap-Assisted spatial attention and scale-Aware layer attention

Ju, L., Kittler, J., Rana, M. F. I., Yang, W., & Feng, Z. (2023) · Pattern Recognition · doi:10.1016/j.patcog.2023.109553 · Cited by 18 · see citing works

SmileNet: Registration-Free Smiling Face Detection In The Wild

Jang, Y., Güneş, H., & Patras, I. (2017) · IEEE International Conference on Computer Vision Workshops · doi:10.1109/iccvw.2017.186 · Cited by 18 · see citing works

DAFE-FD: Density Aware Feature Enrichment for Face Detection

Sindagi, V. A., & Patel, V. M. (2019) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv.2019.00236 · Cited by 18 · see citing works

TCM: Temporal Consistency Model for Head Detection in Complex Videos

Khan, S. D., Altamimi, A. B., Ullah, M., Ullah, H., & Cheikh, F. A. (2020) · Journal of Sensors · doi:10.1155/2020/8861296 · Cited by 17 · see citing works

Small-Scale Face Detection Based on Improved R-FCN

Tang, C., Chen, S., Zhou, X., Ruan, S., & Wen, H. (2020) · Applied Sciences · doi:10.3390/app10124177 · Cited by 17 · see citing works

Context-Aware Region-Dependent Scale Proposals for Scale-Optimized Object Detection Using Super-Resolution

Akita, K., & Ukita, N. (2023) · IEEE Access · doi:10.1109/access.2023.3329302 · Cited by 16 · see citing works

Feature Enhancement for Multi-scale Object Detection

Zheng, H., Chen, J., Chen, L., Li, Y., & Yan, Z. (2020) · Neural Processing Letters · doi:10.1007/s11063-019-10182-x · Cited by 15 · see citing works

Progressively Refined Face Detection Through Semantics-Enriched Representation Learning

Li, Z., Tang, X., Wu, X., Liu, J., & He, R. (2019) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2019.2941800 · Cited by 14 · see citing works

HAMBox: Delving into Online High-quality Anchors Mining for Detecting Outer FacesPreprint

Liu, Y., Tang, X., Wu, X., Han, J., Liu, J., & Ding, E. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1912.09231 · Cited by 14 · see citing works

Multiscale Dynamic Curvelet Scattering Network

Gao, J., Jiao, L., Liu, X., Li, L., Chen, P., Liu, F., & Yang, S. (2022) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2022.3223212 · Cited by 13 · see citing works

Multi-Scale Person Localization With Multi-Stage Deep Sequential Framework

Khan, S. D., & Basalamah, S. M. (2021) · International Journal of Computational Intelligence Systems · doi:10.2991/ijcis.d.210326.001 · Cited by 13 · see citing works

Adaptive dynamic networks for object detection in aerial images

Wu, Z., & Yan, H. (2022) · Pattern Recognition Letters · doi:10.1016/j.patrec.2022.12.022 · Cited by 10 · see citing works

Instance segmentation of faces and mouth-opening degrees based on improved YOLOv8 method

Fan, Y., Zhang, L., Zheng, C., Wang, X., Zhu, J., & Wang, L. (2024) · Multimedia Systems · doi:10.1007/s00530-024-01472-z · Cited by 11 · see citing works

A Region Generation based Model for Occluded Face Detection

Qi, J., Mu, C., Tian, L., & Ran, F. (2020) · Procedia Computer Science · doi:10.1016/j.procs.2020.06.114 · Cited by 11 · see citing works

An Efficient Multi-Scale Anchor Box Approach to Detect Partial Faces from a Video Sequence

Garg, D., Jain, P., Kotecha, K. V., Goel, P., & Varadarajan, V. (2022) · Big Data and Cognitive Computing · doi:10.3390/bdcc6010009 · Cited by 11 · see citing works

1st Place Solutions for OpenImage2019 -- Object Detection and Instance SegmentationPreprint

Liu, Y., Song, G., Zang, Y., Gao, Y., Xie, E., Yan, J., Loy, C. C., & Wang, X. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2003.07557 · Cited by 11 · see citing works

A Review of Cross-Modal Image–Text Retrieval in Remote Sensing

Xu, L., Wang, L., Zhang, J., Ha, D., & Zhang, H. (2025) · Remote Sensing · doi:10.3390/rs17243995 · Cited by 11 · see citing works

Robust appearance modeling for object detection and tracking: a survey of deep learning approaches

Mumuni, A., & Mumuni, F. (2022) · Progress in Artificial Intelligence · doi:10.1007/s13748-022-00290-6 · Cited by 8 · see citing works

Context-Anchors for Hybrid Resolution Face Detection

Wu, T., Liang, D., Pan, J., & Kaneko, S. (2019) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2019.8803548 · Cited by 8 · see citing works

KPNet: Towards Minimal Face Detector

Song, G., Liu, Y., Zang, Y., Wang, X., Leng, B., & Yuan, Q. (2020) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v34i07.6878 · Cited by 7 · see citing works

Object features and face detection performance: Analyses with 3D-rendered synthetic data

Han, J., Karaoğlu, S., Lê, H.-Â., & Gevers, T. (2021) · Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition · doi:10.1109/icpr48806.2021.9412915 · Cited by 7 · see citing works

Exploring Multi-Branch and High-Level Semantic Networks for Improving Pedestrian DetectionPreprint

Cao, J., Pang, Y., & Li, X. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1804.00872 · Cited by 7 · see citing works

Real-time and accurate detection for face and mouth openings in meal-assisting robotics

Fan, Y., Zhang, L., Zheng, C., Wang, Z., Zhu, J., & Wang, X. (2024) · Signal Image and Video Processing · doi:10.1007/s11760-024-03543-0 · Cited by 6 · see citing works

Aggregation Connection Network For Tiny Face Detection

Zhang, C., Li, T., Guo, S., Li, N., Gao, Y., & Wang, K. (2019) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn.2019.8852083 · Cited by 6 · see citing works

A Defects Detection System for Substation Based on YOLOX

Cui, Y., Huang, X., Zhang, X., Ye, J., & Zhong, L. (2022) · IEEE International Electrical and Energy Conference (CIEEC) · doi:10.1109/cieec54735.2022.9846606 · Cited by 6 · see citing works

DeFRCN-MAM: DeFRCN and multi-scale attention mechanism-based industrial defect detection method

Zheng, T., Sa, L., Yu, C., & Song, A. (2024) · Applied Artificial Intelligence · doi:10.1080/08839514.2024.2349981 · Cited by 6 · see citing works

Region-dependent Scale Proposals for Super-Resolution in Object Detection

Akita, K., Haris, M., & Ukita, N. (2020) · IEEE International Conference on Image Processing, Applications and Systems (IPAS) · doi:10.1109/ipas50080.2020.9334961 · Cited by 6 · see citing works

Learning to realign hierarchy for image segmentation

Adão, M. M., Guimarães, S. J. F., & Patrocínio, Z. K. G. (2020) · Pattern Recognition Letters · doi:10.1016/j.patrec.2020.03.010 · Cited by 5 · see citing works

Evaluation of Scale-Aware Realignments of Hierarchical Image Segmentation

Adão, M. M., Guimarães, S. J. F., & Patrocínio, Z. K. G. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-13469-3_17 · Cited by 4 · see citing works

Face-Mask Detection to Control the COVID-19 Spread Employing Deep Learning Approach

Nujella, R. B. P., Sahu, S., & Prakash, S. (2021) · International Conference on Information Systems and Computer Networks (ISCON) · doi:10.1109/iscon52037.2021.9702461 · Cited by 4 · see citing works

Blockchain-enhanced secure guard: a deep Q network framework for robust IoT surveillance person detection

Bethu, S., & Erukala, S. B. (2025) · Cluster Computing · doi:10.1007/s10586-024-04935-0 · Cited by 4 · see citing works

Mask-Net: A Hardware-efficient Object Detection Network with Masked Region Proposals

Chen, H., & Hao, C. (2022) · IEEE International Conference on Application-specific Systems, Architectures and Processors (ASAP) · doi:10.1109/asap54787.2022.00030 · Cited by 4 · see citing works

A Sample-Free Compilation Framework for Efficient Dynamic Tensor Computation

Zhou, Y., Zhu, H., Qiu, Q., Cui, W., Liu, Z., Chen, P., Wahib, M., Guo, C., Feng, S. M., Meng, J., et al. (2025) · International Conference for High Performance Computing, Networking, Storage and Analysis (SC) · doi:10.1145/3712285.3759779 · Cited by 3 · see citing works

Accelerating Proposal Generation Network for Fast Face Detection on Mobile Devices

Zhang, H., Wang, X., Zhu, J., & Kuo, C. ‐. J. (2018) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2018.8451737 · Cited by 3 · see citing works

ElHBiAt: Electra Pre-Training Network Hybrid of BiLSTM, the Attention Layer to Aspect-Based Sentiment Analysis

Nezhad, A. G., Jahanbin, K., & Yamchi, A. R. (2025) · IEEE Access · doi:10.1109/access.2025.3568484 · Cited by 3 · see citing works

A Survey: Crowds Detection Method on Public Transportation

Leone, D. A., Novianto, H., Setiawan, R., Gilbert, T., & Hanafiah, N. (2021) · doi:10.1109/iccsai53272.2021.9609731 · Cited by 3 · see citing works

Aircraft Detection in Remote Sensing Images Based on Background Filtering and Scale Prediction

Gao, J., Li, H., Han, Z., Wang, S., & Hu, X. (2018) · Lecture notes in computer science · doi:10.1007/978-3-319-97304-3_46 · Cited by 3 · see citing works

Improving Face Detection Performance with 3D-Rendered Synthetic DataPreprint

Han, J., Karaoğlu, S., Lê, H.-Â., & Gevers, T. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1812.07363 · Cited by 3 · see citing works

Scale Semantic Flow Preserving Across Image Pyramid

Lin, Z., Song, G., & Leng, B. (2021) · Communications in computer and information science · doi:10.1007/978-3-030-92307-5_54 · Cited by 2 · see citing works

Selective feature block and joint IoU loss for object detection

Wang, J., Hua, R., Jiang, X., Song, K., Meng, Q., & Saada, M. (2024) · Transactions of the Institute of Measurement and Control · doi:10.1177/01423312241261087 · Cited by 2 · see citing works

Face Detection through Scale-Friendly Deep Convolutional NetworksPreprint

Yang, S., Xiong, Y., Loy, C. C., & Tang, X. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1706.02863 · Cited by 104 · see citing works

Single-Shot Scale-Aware Network for Real-Time Face Detection

Zhang, S., Wen, L., Shi, H., Lei, Z., Lyu, S., & Li, S. Z. (2019) · International Journal of Computer Vision · doi:10.1007/s11263-019-01159-3 · Cited by 50 · see citing works

Multi-scale Fully Convolutional Network for Face Detection in the Wild

Bai, Y., & Ghanem, B. (2017) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw.2017.259 · Cited by 18 · see citing works

SFA: Small Faces Attention Face Detector

Luo, S. G., Li, X., Zhu, R., & Zhang, X. (2019) · IEEE Access · doi:10.1109/access.2019.2955757 · Cited by 22 · see citing works

Single Shot Attention-Based Face Detector

Zhuang, C., Zhang, S., Zhu, X., Lei, Z., & Li, S. Z. (2018) · Lecture notes in computer science · doi:10.1007/978-3-319-97909-0_31 · Cited by 6 · see citing works