MRFTrans: Multimodal representation fusion transformer for monocular 3D semantic scene completion

Deep Residual Learning for Image Recognition

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Attention Is All You Need

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MizAR 60 for Mizar 50

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Swin Transformer: Hierarchical Vision Transformer using Shifted Windows

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An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

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Are we ready for autonomous driving? The KITTI vision benchmark suite

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Decoupled Weight Decay Regularization

Loshchilov, I., & Hutter, F. (2017) · arXiv · doi:10.48550/arxiv.1711.05101 · Cited by 12,522 · see citing works

Indoor segmentation and support inference from rgbd images

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Pyramid Vision Transformer: A Versatile Backbone for Dense Prediction without Convolutions

Wang, W., Xie, E., Li, X., Fan, D.-P., Song, K., Liang, D., Lu, T., Luo, P., & Shao, L. (2021) · 2021 IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv48922.2021.00061 · Cited by 5,259 · see citing works

Transformers in Vision: A Survey

Khan, S., Naseer, M., Hayat, M., Zamir, S. W., Khan, F. S., & Shah, M. (2022) · ACM Computing Surveys · doi:10.1145/3505244 · Cited by 3,595 · see citing works

CvT: Introducing Convolutions to Vision Transformers

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2013 IEEE Conference on Computer Vision and Pattern Recognition

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SemanticKITTI: A Dataset for Semantic Scene Understanding of LiDAR Sequences

Behley, J., Garbade, M., Milioto, A., Quenzel, J., Behnke, S., Stachniss, C., & Gall, J. (2019) · 2019 IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2019.00939 · Cited by 2,294 · see citing works

Deformable DETR: Deformable Transformers for End-to-End Object Detection

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2013 IEEE 10th International Symposium on Biomedical Imaging

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BEVFormer: Learning Bird's-Eye-View Representation from Multi-Camera Images via Spatiotemporal Transformers

Li, Z., Wang, W., Li, H., Xie, E., Sima, C., Lu, T., Yu, Q., & Dai, J. (2022) · arXiv · doi:10.48550/arxiv.2203.17270 · Cited by 1,419 · see citing works

Semantic Scene Completion from a Single Depth Image

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2015 International Conference on 3D Vision

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ACFNet: Attentional Class Feature Network for Semantic Segmentation

Zhang, F., Chen, Y., Li, Z., Hong, Z., Liu, J., Ma, F., Han, J., & Ding, E. (2019) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2019.00690 · Cited by 324 · see citing works

MonoScene: Monocular 3D Semantic Scene Completion

Cao, A.-Q., & de Charette, R. (2022) · 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/cvpr52688.2022.00396 · Cited by 301 · see citing works

Learning Affinity from Attention: End-to-End Weakly-Supervised Semantic Segmentation with Transformers

Ru, L., Zhan, Y., Yu, B., & Du, B. (2022) · 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/cvpr52688.2022.01634 · Cited by 299 · see citing works

Sparse Single Sweep LiDAR Point Cloud Segmentation via Learning Contextual Shape Priors from Scene Completion

Xu, Y. L., Gao, J., Li, J., Zhang, R., Li, Z., Huang, R., & Cui, S. R. (2021) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v35i4.16419 · Cited by 291 · see citing works

VoxFormer: Sparse Voxel Transformer for Camera-Based 3D Semantic Scene Completion

Li, Y., Yu, Z., Choy, C., Xiao, C., Álvarez, J. M., Fidler, S., Feng, C., & Anandkumar, A. (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/cvpr52729.2023.00877 · Cited by 252 · see citing works

Point-cloud based 3D object detection and classification methods for self-driving applications: A survey and taxonomy

Fernandes, D., Silva, A., Névoa, R., Simões, C., Gonzalez, D. G., Guevara, M., Novais, P., Monteiro, J., & Melo-Pinto, P. (2021) · Information Fusion · doi:10.1016/j.inffus.2020.11.002 · Cited by 240 · see citing works

TS-CAM: Token Semantic Coupled Attention Map for Weakly Supervised Object Localization

Gao, W., Wan, F., Pan, X., Peng, Z., Tian, Q. C., Han, Z., Zhou, B., & Ye, Q. (2021) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv48922.2021.00288 · Cited by 236 · see citing works

Multiscale spatial–spectral transformer network for hyperspectral and multispectral image fusion

Jia, S., Min, Z., & Fu, X. (2023) · Information Fusion · doi:10.1016/j.inffus.2023.03.011 · Cited by 187 · see citing works

LMSCNet: Lightweight Multiscale 3D Semantic CompletionPreprint

Rold\~ao, L., de Charette, R., & Verroust-Blondet, A. (2020) · arXiv (Cornell University) · Cited by 170 · see citing works

Completing 3D object shape from one depth image

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Anisotropic Convolutional Networks for 3D Semantic Scene Completion

Li, J., Han, K., Wang, P., Liu, Y., & Yuan, 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/cvpr42600.2020.00341 · Cited by 144 · see citing works

MobileStereoNet: Towards Lightweight Deep Networks for Stereo Matching

Shamsafar, F., Woerz, S., Rahim, R., & Zell, A. (2022) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv51458.2022.00075 · Cited by 140 · see citing works

Learning Superpixels with Segmentation-Aware Affinity Loss

Tu, W.-C., Liu, M.-Y., Jampani, V., Sun, D., Chien, S., Yang, M., & Kautz, 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.2018.00066 · Cited by 138 · see citing works

3D Sketch-Aware Semantic Scene Completion via Semi-Supervised Structure Prior

Chen, X., Lin, K.-Y., Qian, C., Zeng, G., & Li, 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/cvpr42600.2020.00425 · Cited by 133 · see citing works

NDC-Scene: Boost Monocular 3D Semantic Scene Completion in Normalized Device Coordinates Space

Yao, J., Li, C., Sun, K., Cai, Y., Li, H., Ouyang, W., & Li, H. (2023) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv51070.2023.00867 · Cited by 132 · see citing works

3D Semantic Scene Completion: A Survey

Roldão, L., de Charette, R., & Verroust-Blondet, A. (2022) · International Journal of Computer Vision · doi:10.1007/s11263-021-01504-5 · Cited by 113 · see citing works

SCPNet: Semantic Scene Completion on Point Cloud

Xia, Z., Liu, Y., Li, X. S., Zhu, X., Ma, Y., Li, Y., Hou, Y., & Qiao, 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/cvpr52729.2023.01692 · Cited by 101 · see citing works

Two Stream 3D Semantic Scene Completion

Garbade, M., Chen, Y.-T., Sawatzky, J., & Gall, J. (2019) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw.2019.00055 · Cited by 99 · see citing works

Semantic Scene Completion Using Local Deep Implicit Functions on LiDAR Data

Rist, C. B., Emmerichs, D., Enzweiler, M., & Gavrila, D. M. (2021) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2021.3095302 · Cited by 99 · see citing works

RGBD Based Dimensional Decomposition Residual Network for 3D Semantic Scene Completion

Li, J., Liu, Y., Gong, D., Shi, Q., Yuan, X., Zhao, C., & Reid, I. D. (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.2019.00788 · Cited by 96 · see citing works

M$^2$BEV: Multi-Camera Joint 3D Detection and Segmentation with Unified Birds-Eye View RepresentationPreprint

Xie, E., Yu, Z., Zhou, D., Philion, J., Anandkumar, A., Fidler, S., Luo, P., & Álvarez, J. M. (2022) · arXiv (Cornell University) · doi:10.48550/arxiv.2204.05088 · Cited by 86 · see citing works

See and Think: Disentangling Semantic Scene Completion

Liu, S., Hu, Y. H., Zeng, Y., Tang, Q., Jin, B., Han, Y., & Li, X. (2018) · neural information processing systems · Cited by 84 · see citing works

Instance Level Affinity-Based Transfer for Unsupervised Domain Adaptation

Sharma, A., Kalluri, T., & Chandraker, M. K. (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/cvpr46437.2021.00532 · Cited by 83 · see citing works

Shape-Former: Bridging CNN and Transformer via ShapeConv for multimodal image matching

Chen, J., Chen, X., Chen, S., Liu, Y., Rao, Y., Yang, Y., Wang, H., & Wu, D. (2022) · Information Fusion · doi:10.1016/j.inffus.2022.10.030 · Cited by 77 · see citing works

BCINet: Bilateral cross-modal interaction network for indoor scene understanding in RGB-D images

Zhou, W., Yue, Y., Fang, M., Qian, X., Yang, R., & Yu, L. (2023) · Information Fusion · doi:10.1016/j.inffus.2023.01.016 · Cited by 76 · see citing works

Multi-modal policy fusion for end-to-end autonomous driving

Huang, Z., Sun, S., Zhao, J., & Mao, L. (2023) · Information Fusion · doi:10.1016/j.inffus.2023.101834 · Cited by 74 · see citing works

Adaptive Affinity Loss and Erroneous Pseudo-Label Refinement for Weakly Supervised Semantic Segmentation

Zhang, X., Peng, Z., Zhu, P., Zhang, T., Li, C., Zhou, H., & Jiao, L. (2021) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3474085.3475675 · Cited by 59 · see citing works

SCFusion: Real-time Incremental Scene Reconstruction with Semantic Completion

Wu, S.-C., Tateno, K., Navab, N., & Tombari, F. (2020) · International Conference on 3D Vision (3DV) · doi:10.1109/3dv50981.2020.00090 · Cited by 40 · see citing works

OccDepth: A Depth-Aware Method for 3D Semantic Scene CompletionPreprint

Miao, R., Liu, W., Chen, M., Gong, Z., Xu, W., Chen, H., & Zhou, S. (2023) · arXiv (Cornell University) · doi:10.48550/arxiv.2302.13540 · Cited by 38 · see citing works

Pseudo information measure: a new concept for extension of Bayesian fusion in robotic map building

Moshiri, B., Asharif, M. R., & Hoseinnezhad, R. (2002) · Information Fusion · doi:10.1016/s1566-2535(01)00055-0 · Cited by 31 · see citing works

2D–3D Geometric Fusion network using Multi-Neighbourhood Graph Convolution for RGB-D indoor scene classification

Mosella-Montoro, A., & Ruiz-Hidalgo, J. (2021) · Information Fusion · doi:10.1016/j.inffus.2021.05.002 · Cited by 30 · see citing works

DepthSSC: Monocular 3D Semantic Scene Completion via Depth-Spatial Alignment and Voxel Adaptation

Yao, J., Zhang, J., Pan, X., Wu, T., & Xiao, C. (2025) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv61041.2025.00216 · Cited by 29 · see citing works

Granger causality-based information fusion applied to electrical measurements from power transformers

Rodríguez-Rivero, J., Ramı́rez, J., Martínez-Murcia, F. J., Segovia, F., Ortíz, A., Salas-Gonzalez, D., Castillo-Barnés, D., Illán, I. A., Puntonet, C. G., Jiménez-Mesa, C., et al. (2019) · Information Fusion · doi:10.1016/j.inffus.2019.12.005 · Cited by 21 · see citing works

Semantic-Relation Transformer for Visible and Infrared Fused Image Quality Assessment

Chang, Z., Yang, S., Feng, Z., Gao, Q., Wang, S., & Cui, Y. (2023) · Information Fusion · doi:10.1016/j.inffus.2023.02.021 · Cited by 17 · see citing works

A sensor fusion approach to MARG module orientation estimation for a real-time hand tracking application

Ratchatanantakit, N., O-larnnithipong, N., Sonchan, P., Adjouadi, M., & Barreto, A. B. (2022) · Information Fusion · doi:10.1016/j.inffus.2022.09.017 · Cited by 12 · see citing works

DepthSSC: Monocular 3D Semantic Scene Completion via Depth-Spatial Alignment and Voxel AdaptationPreprint

Yao, J., Zhang, J., Pan, X., et al. (2023) · arXiv (Cornell University) · doi:10.48550/arxiv.2311.17084 · Cited by 11 · see citing works

An Attention-Based Hybrid Deep Learning Framework Integrating Temporal Coherence And Dynamics For Discriminating Schizophrenia

Zhao, M., Yan, W., Xu, R., Zhi, D., Jiang, R., Jiang, T., Calhoun, V. D., & Jing Sui （Beijing Normal University）， my correct affiliation is beijing normal university, N. Q. U. O. S. A. T. (2021) · IEEE International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi48211.2021.9433919 · Cited by 11 · see citing works

Real-time path planning to dispatch a mobile sensor into an operational area

Kim, Y., Jung, W., & Bang, H. (2018) · Information Fusion · doi:10.1016/j.inffus.2018.01.010 · Cited by 9 · see citing works

Multimodal fusion and vision–language models: A survey for robot vision

Han, X., Chen, S., Fu, Z., Feng, Z., Fan, L., An, D., Wang, C., Guo, L., Meng, W., Zhang, X., et al. (2026) · Information Fusion · doi:10.1016/j.inffus.2025.103652 · Cited by 41 · see citing works

PSTNet: Enhanced Polyp Segmentation With Multi-Scale Alignment and Frequency Domain Integration

Xu, W., Xu, R., Wang, C., Li, X., Xu, S., & Guo, L. (2024) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2024.3421550 · Cited by 25 · see citing works

Segment Anything Model Is a Good Teacher for Local Feature Learning

Wu, J., Xu, R., Wood-Doughty, Z., Wang, C., Xu, S., & Lam, E. Y. M. (2025) · IEEE Transactions on Image Processing · doi:10.1109/tip.2025.3554033 · Cited by 16 · see citing works

Context-driven and sparse decoding for Remote Sensing Visual Grounding

Zhao, Y., Chen, Y., Yao, R., Xiong, S., & Lu, X. (2025) · Information Fusion · doi:10.1016/j.inffus.2025.103296 · Cited by 15 · see citing works

Generalization Boosted Adapter for Open-Vocabulary Segmentation

Xu, W., Wang, C., Feng, X., Xu, R., Huang, L., Zhang, Z., Guo, L., & Xu, S. (2024) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2024.3454227 · Cited by 11 · see citing works

CDF-DSR: Learning continuous depth field for self-supervised RGB-guided depth map super resolution

Zhang, S., Dong, J., Ma, Y., Cai, H., Wang, M., Li, Y., Kabika, T. B., Li, X., & Hou, W. W. (2024) · Information Fusion · doi:10.1016/j.inffus.2024.102884 · Cited by 7 · see citing works

UASeg: Uncertainty aware weakly supervised semantic segmentation for autonomous driving

Li, Y., Hu, C., Ren, K., Xi, H., & Fan, J. (2025) · Expert Systems with Applications · doi:10.1016/j.eswa.2025.128609 · Cited by 6 · see citing works

Modality-aligned anchor learning based on multi-level fusion for accurate scene graph generation

Yang, J., He, Y., Yang, J., Yang, L. T., Gao, Y., & Dai, C. (2025) · Information Fusion · doi:10.1016/j.inffus.2025.103755 · Cited by 4 · see citing works

A Multi-Modal Transformer Optimized Object Identification Model for Passenger Safety in Ridesharing Vehicles

Jaiswal, P., Menon, U. B., Mishra, S., Mishra, N., & Alkhayyat, A. H. (2024) · International Conference on Intelligent Computing and Emerging Communication Technologies (ICEC) · doi:10.1109/icec59683.2024.10837164 · Cited by 4 · see citing works

Geometry-semantic aware for monocular 3D Semantic Scene Completion

Lu, Z., Cao, B., Xia, S., & Hu, Q. (2024) · Pattern Recognition · doi:10.1016/j.patcog.2024.111030 · Cited by 3 · see citing works

RF-Fusion: Robust and fine-grained volumetric panoptic mapping system with multi-level data fusion for robots

Zhang, J., Yuan, X., Wang, C., Song, Y. H., Nie, W., Zhou, F., & Sheng, W. (2025) · Information Fusion · doi:10.1016/j.inffus.2025.103209 · Cited by 2 · see citing works

Deep Learning for 3-D Lane Detection in Autonomous Driving: A Survey

Teng, X., Chen, Z., Chen, S., Zhang, Z., Xu, S., Hao, Z., Guo, D., & Li, H. (2026) · IEEE Internet of Things Journal · doi:10.1109/jiot.2026.3654005 · Cited by 2 · see citing works

A Novel Orthogonal Halbach Bilayer for Super-Resolution Tactile Perception

Gui, M.-J., Zhou, X.-H., Xie, X., Liu, S.-Q., Wang, S., Liao, H.-C., Xiang, T., Huang, D.-X., Yao, B.-X., & Hou, Z. (2025) · IEEE/ASME Transactions on Mechatronics · doi:10.1109/tmech.2025.3573731 · Cited by 2 · see citing works

DFSplat: High‐Quality 3D Gaussian Splatting From Sparse Multi‐View Images Based on Feature Fusion

Gao, Q., Xu, B., Wang, C., Wang, L., & Zhang, L. (2025) · Concurrency and Computation Practice and Experience · doi:10.1002/cpe.70521 · Cited by 1 · see citing works

RML: Efficient Representation Mutual Learning Framework for End-to-End Weakly Supervised Semantic Segmentation

Xu, R., Wang, C., Xu, S., Meng, W., & Zhang, X. (2025) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2025.3545166 · Cited by 1 · see citing works

Editorial: Transformer models for multi-source visual fusion and understanding

Ning, X., Bai, X. P., Tiwari, P., Zhou, J. W., Kim, B., & Xiao, Y. (2025) · Information Fusion · doi:10.1016/j.inffus.2025.103112

Human-Oriented Production Safety Control Technology of Digital Twin Workshop

Li, H., & Wang, H. (2025) · Springer eBooks · doi:10.1007/978-3-031-82170-7_8

OV-BIS: Open-Vocabulary Boundary Guide Zero-Shot 3D Instance Segmentation

Yi, T., Wang, S., Zhang, Z., Wang, C., Dong-ming Yan, A., Xu, R., & Chen, E. (2025) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2025.3599047

Complementary Information Guided Occupancy Prediction via Multi-Level Representation Fusion

Xu, R., Lin, J., Zhou, J., Dong, J., Wang, C., Wang, R., Guo, L., Xu, S., & Liang, X. (2025) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra55743.2025.11128273

MVFormer: UNet-Like Transformer With Mix-Voxel Attention for Camera-Based 3D Semantic Scene Completion

Gao, F., Chen, Y., Wang, K., Zhou, P., & Lǚ, J. (2025) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2025.3619211

Boosting Adversarial Transferability via Commonality-Oriented Gradient Optimization

Gao, Y., Liu, Y., Liu, J., Zhang, Q., Zhang, H., Miao, D., & Zhao, C. (2026) · Lecture notes in computer science · doi:10.1007/978-981-95-5693-9_5

Research on English semantic modeling and understanding algorithm based on the SemBERT model of natural language processing

Zhang, A., Zhang, Y., Xie, H., & Zhang, X. (2026) · Discover Applied Sciences · doi:10.1007/s42452-026-08614-0

Mobile robot inspection of building plenum spaces via vision-based multi-sensor fault detection

Lou, G., Liu, S., Shen, Y., Wong, W. Y., Lu, Y., & Duan, M. (2026) · Automation in Construction · doi:10.1016/j.autcon.2026.106889

Learning accurate monocular 3D voxel representation via bilateral voxel transformer

Cheng, T., Jiang, H., Chen, S., Liao, B., Zhang, Q., Liu, W., & Wang, X. (2024) · Image and Vision Computing · doi:10.1016/j.imavis.2024.105237 · Cited by 4 · see citing works

ET-Former: Efficient Triplane Deformable Attention for 3D Semantic Scene Completion From Monocular Camera

Liang, J., Yin, H., Qi, X., Park, J. J., Sun, M., Madhivanan, R., & Manocha, D. (2025) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros60139.2025.11247407

MonoScene: Monocular 3D Semantic Scene Completion

Cao, A.-Q., & de Charette, R. (2022) · 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/cvpr52688.2022.00396 · Cited by 301 · see citing works

Semantic Scene Completion Through Context Transformer and Recurrent Convolution

Yang, W., Yu, H., & Cao, Y. (2024) · IEEE Access · doi:10.1109/access.2024.3401481

DepthSSC: Monocular 3D Semantic Scene Completion via Depth-Spatial Alignment and Voxel Adaptation

Yao, J., Zhang, J., Pan, X., Wu, T., & Xiao, C. (2025) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv61041.2025.00216 · Cited by 29 · see citing works