World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
72
Citations
26622
World Ranking
1647
National Ranking
223

Overview

Limin Wang is affiliated with Nanjing University in China and specializes in the field of Computer Science, with a particular focus on subfields such as Computer Vision and Pattern Recognition, Artificial Intelligence, Control and Systems Engineering, Computer Graphics and Computer-Aided Design, and Computational Theory and Mathematics.

Their research addresses key topics including Human Pose and Action Recognition, Multimodal Machine Learning Applications, Anomaly Detection Techniques and Applications, Domain Adaptation and Few-Shot Learning, Video Surveillance and Tracking Methods, Advanced Image and Video Retrieval Techniques, and Advanced Neural Network Applications.

Limin Wang has published extensively, with recurring appearances in certain publication venues. Frequent venues include arXiv (Cornell University) with 105 publications, IEEE Transactions on Pattern Analysis and Machine Intelligence with 10 publications, the 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) with 7 publications, the International Journal of Computer Vision with 7 publications, and the 2021 IEEE/CVF International Conference on Computer Vision (ICCV) with 6 publications.

Recent notable papers by Limin Wang include:

  • MixFormer: End-to-End Tracking with Iterative Mixed Attention, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • A review of convolutional neural networks in computer vision, 2024, Artificial Intelligence Review
  • VideoMAE: Masked Autoencoders are Data-Efficient Learners for Self-Supervised Video Pre-Training, 2022, arXiv (Cornell University)
  • PyMAF: 3D Human Pose and Shape Regression with Pyramidal Mesh Alignment Feedback Loop, 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • TEINet: Towards an Efficient Architecture for Video Recognition, 2020, Proceedings of the AAAI Conference on Artificial Intelligence

The scientist collaborates frequently with several co-authors, including Gangshan Wu (53 co-authored papers), Yu Qiao (27), Yali Wang (22), Zhaoyang Liu (11), and Kunchang Li (10).

Best Publications

  • Temporal Segment Networks: Towards Good Practices for Deep Action Recognition

    Limin Wang;Yuanjun Xiong;Zhe Wang;Yu Qiao

  • Action recognition with trajectory-pooled deep-convolutional descriptors

    Limin Wang;Yu Qiao;Xiaoou Tang

  • Temporal Segment Networks for Action Recognition in Videos

    Limin Wang;Yuanjun Xiong;Zhe Wang;Yu Qiao

  • Bag of visual words and fusion methods for action recognition

    Xiaojiang Peng;Limin Wang;Xingxing Wang;Yu Qiao

  • MixFormer: End-to-End Tracking with Iterative Mixed Attention

    Unknown

  • VideoMAE: Masked Autoencoders are Data-Efficient Learners for Self-Supervised Video Pre-Training

    Unknown

  • Temporal Action Detection with Structured Segment Networks

    Yue Zhao;Yuanjun Xiong;Limin Wang;Zhirong Wu

  • A review of convolutional neural networks in computer vision

    Unknown

  • TEA: Temporal Excitation and Aggregation for Action Recognition

    Yan Li;Bin Ji;Xintian Shi;Jianguo Zhang

  • UntrimmedNets for Weakly Supervised Action Recognition and Detection

    Limin Wang;Yuanjun Xiong;Dahua Lin;Luc Van Gool

  • Towards Good Practices for Very Deep Two-Stream ConvNets

    Limin Wang;Yuanjun Xiong;Zhe Wang;Yu Qiao

  • Real-Time Action Recognition with Enhanced Motion Vector CNNs

    Bowen Zhang;Limin Wang;Zhe Wang;Yu Qiao

  • TDN: Temporal Difference Networks for Efficient Action Recognition

    Unknown

  • Appearance-and-Relation Networks for Video Classification

    Limin Wang;Wei Li;Luc Van Gool

  • Temporal Segment Networks: Towards Good Practices for Deep Action Recognition

    Limin Wang;Yuanjun Xiong;Zhe Wang;Yu Qiao

  • VideoMAE V2: Scaling Video Masked Autoencoders with Dual Masking

    Unknown

  • PyMAF: 3D Human Pose and Shape Regression With Pyramidal Mesh Alignment Feedback Loop

    Hongwen Zhang;Yating Tian;Xinchi Zhou;Wanli Ouyang

  • Learning Actor Relation Graphs for Group Activity Recognition

    Unknown

  • TEINet: Towards an Efficient Architecture for Video Recognition

    Zhaoyang Liu;Donghao Luo;Yabiao Wang;Limin Wang

  • Multi-view Super Vector for Action Recognition

    Zhuowei Cai;Limin Wang;Xiaojiang Peng;Yu Qiao

  • Motionlets: Mid-level 3D Parts for Human Motion Recognition

    LiMin Wang;Yu Qiao;Xiaoou Tang

  • Temporal Action Detection with Structured Segment Networks

    Yue Zhao;Yuanjun Xiong;Yuanjun Xiong;Limin Wang;Zhirong Wu;Zhirong Wu

  • A comparative study of encoding, pooling and normalization methods for action recognition

    Xingxing Wang;LiMin Wang;Yu Qiao

  • CUHK & ETHZ & SIAT Submission to ActivityNet Challenge 2016.

    Yuanjun Xiong;Limin Wang;Zhe Wang;Bowen Zhang

  • Real-Time Action Recognition With Deeply Transferred Motion Vector CNNs

    Bowen Zhang;Limin Wang;Zhe Wang;Yu Qiao

  • Knowledge Guided Disambiguation for Large-Scale Scene Classification With Multi-Resolution CNNs

    Limin Wang;Sheng Guo;Weilin Huang;Yuanjun Xiong

  • A Pursuit of Temporal Accuracy in General Activity Detection

    Yuanjun Xiong;Yue Zhao;Limin Wang;Dahua Lin

  • Video Action Detection with Relational Dynamic-Poselets

    Limin Wang;Limin Wang;Yu Qiao;Xiaoou Tang;Xiaoou Tang

  • Places205-VGGNet Models for Scene Recognition

    Limin Wang;Sheng Guo;Weilin Huang;Yu Qiao

Frequent Co-Authors

Yu Qiao
Yu Qiao Chinese Academy of Sciences
Xiaoou Tang
Xiaoou Tang Chinese University of Hong Kong
Luc Van Gool
Luc Van Gool Institute for Computer Science, Artificial Intelligence and Technology (INSAIT)
Dahua Lin
Dahua Lin Chinese University of Hong Kong
Otmar Hilliges
Otmar Hilliges ETH Zurich
Wen Li
Wen Li University of Electronic Science and Technology of China
Rahul Sukthankar
Rahul Sukthankar Google (United States)
Abhinav Gupta
Abhinav Gupta Carnegie Mellon University

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