Limin Wang (王利民)
Multimedia Computing Group
Department of Computer Science and Technology
Nanjing University
Office: CS Building 506
Email: lmwang.nju [at] gmail.com

About Me (CV)

I am a Professor at Department of Computer Science and Technology and also affiliated with State Key Laboratory for Novel Software Technology, Nanjing University.

Previously, I received the B.S. degree from Nanjing University in 2011, and the Ph.D. degree from The Chinese University of Hong Kong under the supervision of Prof. Xiaoou Tang in 2015. From 2015 to 2018, I was a Post-Doctoral Researcher with Prof. Luc Van Gool in the Computer Vision Laboratory (CVL) at ETH Zurich.

News

  • 2024-01-15: Two papers (InternVid & SparseFormer) are accepted by ICLR 2024.
  • 2024-01-01: The extension of MixFormer is accepted by T-PAMI.
  • 2023-11-30: Our LogN is accepted by IJCV.
  • 2023-11-01: Our CamLiFlow is accepted by T-PAMI.
  • 2023-11-01: Our RefineTAD receives the Best Paper Honorable Mention Award of ACM MM 2023.
  • 2023-10-25: Our Dynamic MDETR is accepted by T-PAMI.
  • 2023-09-22: Our MixFormer V2 is accepted by NeurIPS 2023.
  • 2023-09-02: One paper on crowded pose estimation is accepted by IJCV.
  • 2023-07-21: Our survey paper on 3D human mesh recovery is accepted by T-PAMI.
  • 2023-07-14: Our UMT Foundation Model is accepted by ICCV 2023.
  • 2023-07-14: Our SportsMOT dataset is accepted by ICCV 2023.
  • 2023-07-14: Ten papers are accepted by ICCV 2023 (Topics: Video foundation models, action detection and anticipation, multi-object tracking, (3D) object detection, new dataset.)
  • 2023-07-13: We release the InterVid dataset for multi-modal video understanding and generation.
  • 2023-06-25: We release the Grasp Anything project for embodied AI by leveraging vision foundation model.
  • 2023-06-15: Prof. Limin Wang is invited to be an Editorial Board Member of IJCV.
  • 2023-06-10: I am invited to give a ARP talk at VALSE 2023 (slide).
  • 2022-05-25: We propose the MixFormer V2, a real-time object tracker. We have released the source code.
  • 2023-05-19: Temporal Perceiver is accepted by T-PAMI. We have released the source code.
  • 2023-05-10: We present the VideoChat system, by combining video foundation model and LLM.
  • 2023-03-18: We propose the VideoMAE V2, training the first billion-level video transformer. We have released the source code.
  • 2023-03-01: Five papers on video understanding and point cloud analysis are accepted by CVPR 2023.
  • 2023-02-01: One paper is accepted by ICLR 2023 and one by AAAI 2023.
  • 2022-11-01: The FineAction dataset is accepted by TIP.
  • 2022-10-09: The extension of LIP is accepted by IJCV.
  • 2022-09-15: VideoMAE and PointTAD are accepted by NeurIPS 2022.
  • 2022-09-15: We present the BasicTAD, an end-to-end TAD baseline method. We have released the source code.
  • 2022-08-10: One paper is accepted by ECCV 2022 and one paper (CDG) is accepted by IJCV.
  • 2022-05-01: We are organizing the second DeeperAction Challenge at ECCV 2022, by introducing five new benchmarks on temporal action localization, multi-actor tracking, spatiotemporal action detection, part-level action parsing, and fine-grained video anomaly recognition.
  • 2022-03-23: We present the VideoMAE, a self-supervised video transformer obtaining SOTA performance on the benchmarks of Kinetics, Something-Something, and AVA. We have released the source code and pre-trained models.
  • 2022-03-02: We present the MixFormer, a compact and efficient object tracker, obtaining SOTA performance on several benchmarks. We have released the source code.
  • 2022-03-02: We present the AdaMixer, a fast-converging query based object detector tracker, obtaining competitive performance on the MS COCCO benchmark. We have released the source code.
  • 2022-03-02: Seven papers on object detection, object tracking, action recognition etc. are accepted by CVPR 2022.
  • 2021-07-25: Eight papers on video understanding are accepted by ICCV 2021: new dataset (MultiSports), backbone (TAM), sampling method (MGSampler), detection frameworks (RTD and TRACE). For more details, please refer to our papers.
  • 2021-07-15: We release the MultiSports dataset for spatiotemporal action detection.
  • 2021-07-15: Our team secures the first place at ACM MM Pre-training for Video Understanding Challenge for Track 2.
  • 2021-06-15: Our team secures the first place at CVPR Kinetics Challenge for Self-Supervised Task.
  • 2021-06-15: Our team secures the first place at CVPR PIC Challenge for Human-Centric Spatio-Temporal Video Grounding Task.
  • 2021-06-01: We are organizing DeeperAction Challenge at ICCV 2021, by introducing three new benchmarks on temporal action localization, spatiotemporal action detection, and part-level action parsing.
  • 2021-04-20: The extension of TRecgNet is accepted by IJCV.
  • 2021-04-07: We propose a target transformer for accurate anchor-free tracking, termed as TREG (code).
  • 2021-04-07: We present a transformer decoder for direct action proposal generation, termed as RTD-Net (code).
  • 2021-03-01: Two papers on action recognition and point cloud segmentation are accepted by CVPR 2021.
  • 2020-12-30: We propose a new video architecture of using temporal difference, termed as TDN and realease the code.
  • 2020-07-03: Three papers on action detection and segmentation are accepted by ECCV 2020.
  • 2020-06-28: Our proposed DSN, a dynamic version of TSN for efficient action recognition, is accepted by TIP.
  • 2020-05-14: We propose a temporal adaptive module for video recognition, termed as TAM and code.
  • 2020-04-16: The code of our published papers will be made available at Github: MCG-NJU.
  • 2020-04-16: We propose a fully convolutional online tracking framwork, termed as FCOT and code.
  • 2020-03-10: Our proposed temporal module TEA is accepted by CVPR 2020.
  • 2020-01-20: We propose an efficient video representation learning framwork, termed as CPD and release the code.
  • 2020-01-15: We present an anchor-free action tubelet detector, termed as MOC-Detector and release the code.
  • 2019-12-20: Our proposed V4D, a principled video-level representation learning framework, is accepted by ICLR 2020.
  • 2019-11-21: Our proposed TEINet, an efficient video architecture for video recognition, is accepted by AAAI 2020.
  • 2019-07-23: Our proposed LIP, a general alternative to average or max pooling, is accepted by ICCV 2019.
  • 2019-03-15: Two papers are accepted by CVPR 2019: one for group activity recognition and one for RGB-D transfer learning.
  • 2018-08-19: One paper is accepted by ECCV 2018 and one (TSN) by T-PAMI.
  • 2018-04-01: I join Nanjing University as a faculty member at Department of Computer Science and Technology.
  • 2017-11-28: We released a recent work on video architecture design for spatiotemporal feature learning. [ arXiv ] [ Code ].
  • 2017-09-08: We have released the TSN models learned in the Kinetics dataset. These models could be transferred well to the existing datasets for action recognition and detection [ Link ].
  • 2017-09-01: One paper is accepted by ICCV 2017 and one (OS2E-CNN) by IJCV.
  • 2017-07-18: I am invited to give a talk at the Workshop on Frontiers of Video Technology-2017 [ Slide ].
  • 2017-03-28: I am co-organizing the CVPR2017 workshop and challenge on Visual Understanding by Learning from Web Data. For more details, please see the workshop page and challenge page.
  • 2017-02-28: Two papers are accepted by CVPR 2017.
  • 2016-12-20: We release the code and models for SR-CNN paper [ Code ].
  • 2016-10-05: We release the code and models for Places2 scene recognition challenge [ arXiv ] [ Code ].
  • 2016-08-03: Code and model of Temporal Segment Networks is released [ arXiv ] [ Code ].
  • 2016-07-15: One paper is accepted by ECCV 2016 and one by BMVC 2016.
  • 2016-06-16: Our team secures the 1st place for untrimmed video classification at ActivityNet Challenge 2016 [ Result ].
    Basically, our solution is based on our works of Temporal Segment Networks (TSN) and Trajectory-pooled Deep-convolutional Descriptors (TDD).
  • 2016-03-01: Two papers are accepted by CVPR 2016.
  • 2015-12-10: Our SIAT_MMLAB team secures the 2nd place for scene recognition at ILSVRC 2015 [ Result ].
  • 2015-09-30: We rank 3rd for cultural event recognition on ChaLearn Looking at People challenge, at ICCV 2015.
  • 2015-08-07: We release the Places205-VGGNet models [ Link ].
  • 2015-07-22: Code of Trajectory-Pooled Deep-onvolutional Descriptors (TDD) is released [ Link ].
  • 2015-07-15: Very deep two stream ConvNets are proposed for action recognition [ Link ].
  • 2015-03-15: We are the 1st winner of both tracks for action recognition and cultural event recognition, on ChaLearn Looking at People Challenge at CVPR 2015.
  • 2015-03-03: One paper is accepted by CVPR 2015, details coming soon.
  • 2014-09-05: We rank 4th for action recognition and 2nd for action detection, on THUMOS'14 Challenge at ECCV 2014.
  • 2014-06-16: Two papers are accepted by ECCV 2014.
  • 2014-06-10: We are the 1st winner of both track 1 and track2, and rank 4th for track3, on ChaLearn Looking at People Challenge at ECCV 2014.
  • 2014-05-20: A comprehensive study paper on action recognition [ Link ].
  • 2014-05-16: New homepage on Github launched!

Selected Publications [ Full List ] [ Google Scholar ] [ Github: MCG-NJU ]

MixFormer: End-to-End Tracking with Iterative Mixed Attention
Y. Cui, C. Jiang, G. Wu, L. Wang
in IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
[ Paper ] [ Code ]
Learning Optical Flow and Scene Flow with Bidirectional Camera-LiDAR Fusion
H.Liu, T. Lu, Y. Xu, J. Liu, L. Wang
in IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023.
[ Paper ] [ Code ]
Dynamic MDETR: A Dynamic Multimodal Transformer Decoder for Visual Grounding
F. Shi, R. Gao, W. Huang, L. Wang
in IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023.
[ Paper ] [ Code ]
Recovering 3D Human Mesh from Monocular Images: A Survey
Y. Tian, H. Zhang, Y. Liu, L. Wang
in IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023.
[ Paper ] [ Code ]
Temporal Perceiver: A General Architecture for Arbitrary Boundary Detection
J. Tan, Y. Wang, G. Wu L. Wang
in IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023.
[ Paper ] [ Code ]
Logit Normalization for Long-tail Object Detection
L. Zhang, Y. Teng, L. Wang
in International Journal of Computer Vision (IJCV), 2023.
[ Paper ] [ Code ]
Dual Graph Networks for Pose Estimation in Crowded Scenes
J. Tu, G. Wu, L. Wang
in International Journal of Computer Vision (IJCV), 2023.
[ Paper ] [ Code ]
LIP: Local Importance-based Pooling
Z. Gao, L. Wang, G. Wu
in International Journal of Computer Vision (IJCV), 2023.
[ Paper ] [ Code ]
VideoMAE V2: Scaling Video Masked Autoencoders with Dual Masking
L. Wang, B. Huang. Z. Zhao, Z. Tong, Y. He, Y. Wang, Y. Wang, Yu Qiao
in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
[ Paper ] [ Code ]
Cross-Domain Gated Learning for Domain Generalization
D. Du, J. Chen, Y. Li, K. Ma, G. Wu, Y Zheng, L. Wang
in International Journal of Computer Vision (IJCV), 2022.
[ Paper ] [ Code ]
VideoMAE: Masked Autoencoders are Data-Efficient Learners for Self-Supervised Video Pre-Training
Z. Tong, Y. Song, J. Wang, L. Wang
in Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS), 2022.
[ Paper ] [ Code ]
MixFormer: End-to-End Tracking with Iterative Mixed Attention
Y. Cui, C. Jiang, L. Wang, G. Wu
in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
[ Paper ] [ Code ]
AdaMixer: A Fast-Converging Query-Based Object Detector
Z. Gao, L. Wang, B. Han, S. Guo
in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
[ Paper ] [ Code ]
Cross-Modal Pyramid Translation for RGB-D Scene Recognition
in International Journal of Computer Vision (IJCV), 2021.
[ Paper ] [ Code ]
MultiSports: A Multi-Person Video Dataset of Spatio-Temporally Localized Sports Actions
Y. Li, L. Chen, R. He, Z. Wang, G. Wu, L. Wang
in IEEE International Conference on Computer Vision (ICCV), 2021.
[ Paper ] [ Data ] [ Code ] [ Challenge ]
TDN: Temporal Difference Networks for Efficient Action Recognition
L. Wang, Z. Tong, B. Ji, G. Wu
in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
[ Paper ] [ Code ]
Temporal Action Detection with Structured Segment Networks
Y. Zhao, Y. Xiong, L. Wang, Z. Wu, X. Tang, and D. Lin
in International Journal of Computer Vision (IJCV), 2020.
[ Paper ] [ Code ]
Actions as Moving Points
Y. Li, Z. Wang, L. Wang, G. Wu
in European Conference on Computer Vision (ECCV), 2020.
[ Paper ] [ Code ]
Temporal Segment Networks for Action Recognition in Videos
L. Wang, Y. Xiong, Z. Wang, Y. Qiao, D. Lin, X. Tang, and L. Van Gool
in IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2019.
[ Paper ] [ Code ]
Transferring Deep Object and Scene Representations for Event Recognition in Still Images
L. Wang, Z. Wang, Y. Qiao, and L. Van Gool
in International Journal of Computer Vision (IJCV), 2018.
[ Paper ] [ Code ]
STOA performance for event recognition on ChaLearn LAP cultural event, WIDER datasets.
Appearance-and-Relation Networks for Video Classification
L. Wang, W. Li, W. Li, and L. Van Gool
in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018.
[ Paper ] [ Code ]
A new architecture for spatiotemporal feature learning.
UntrimmedNets for Weakly Supervised Action Recognition and Detection
L. Wang, Y. Xiong, D. Lin, and L. Van Gool
in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017.
[ Paper ] [ BibTex ][ Code ]
An end-to-end architecture to learn from untrimmed videos.
Temporal Segment Networks: Towards Good Practices for Deep Action Recognition
L. Wang, Y. Xiong, Z. Wang, Y. Qiao, D. Lin, X. Tang, and L. Van Gool
in European Conference on Computer Vision (ECCV), 2016.
[ Paper ] [ BibTex ] [ Poster ] [ Code ] [ Journal Version]
Proposing a segmental architecture and obtaining the state-of-the-art performance on UCF101 and HMDB51
Action Recognition with Trajectory-Pooled Deep-Convolutional Descriptors
L. Wang, Y. Qiao, and X. Tang
in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015.
[ Paper ] [ BibTex ] [ Extended Abstract ] [ Poster ] [ Project Page ] [ Code ]
State-of-the-art performance: HMDB51: 65.9%, UCF101: 91.5%.

Contests

  • ActivityNet Large Scale Activity Recognition Challenge, 2016: Untrimmed Video Classification, Rank: 1/24.
  • ImageNet Large Scale Visual Recognition Challenge, 2015: Scene Recognition, Rank: 2/25.
  • ChaLearn Looking at People Challenge, 2015, Rank: 1/6
  • THUMOS Action Recognition Challenge, 2015, Rank: 5/11.
  • ChaLearn Looking at People Challenge, 2014 , Rank: 1/6, 4/17.
  • THUMOS Action Recognition Challenge, 2014, Rank: 4/14, 2/3.
  • ChaLearn Multi-Modal Gesture Recognition Challenge, 2013 , Rank: 4/54.
  • THUMOS Action Recognition Challenge, 2013, Rank: 4/16.

Academic Service

Journal Reviewer

IEEE Transactions on Pattern Analysis and Machine Intelligence

IEEE Transactions on Image Processing

IEEE Transactions on Multimedia

IEEE Transactions on Circuits and Systems for Video Technology

Pattern Recognition

Pattern Recognition Letter

Image and Vision Computing

Computer Vision and Image Understanding


Conference Reviewer

IEEE Conference on Computer Vision and Pattern Recognition, 2017

IEEE International Conference on Automatic Face and Gesture Recognition, 2017

European Conference on Computer Vision, 2016

Asian Conference on Computer Vision, 2016

International Conference on Pattern Recognition, 2016

Friends

Wen Li (ETH), Jie Song (ETH), Sheng Guo (Malong), Weilin Huang (Malong), Bowen Zhang (USC), Zhe Wang (UCI), Wei Li (Google), Yuanjun Xiong (Amazon), Xiaojiang Peng (SIAT), Zhuowei Cai (Google), Xingxing Wang (NTU)

Last Updated on 15th June., 2023

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