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Ding, Runwei

  1. Contrastive Learning from Extremely Augmented Skeleton Sequences for Self-supervised Action Recognition
    2021/12/07 by Tianyu Guo, Guo, Tianyu, Hong Liu +9 · 8 citations
    Computer Science · Engineering · #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Gait Recognition and Analysis #Human Pose and Action Recognition #Multimodal Machine Learning Applications
  2. A Survey on 3D Skeleton-Based Action Recognition Using Learning Method
    2020/02/14 by Bin Ren, Mengyuan Liu, Ren, Bin +5 · 6 citations
    Computer Science · Engineering · #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Gait Recognition and Analysis #Hand Gesture Recognition Systems #Human Pose and Action Recognition
  3. Co-Evolution of Pose and Mesh for 3D Human Body Estimation from Video
    2023/08/20 by You, Yingxuan, Liu, Hong, Wang, Ti +3 · 7 citations
    #Artificial Intelligence (cs.AI) #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG)
  4. Exploiting Temporal Contexts with Strided Transformer for 3D Human Pose Estimation
    2021/03/26 by Li, Wenhao, Liu, Hong, Ding, Runwei +3 · 5 citations
    #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences
  5. Weakly-supervised 3D Human Pose Estimation with Cross-view U-shaped Graph Convolutional Network
    2021/05/23 by Hua, Guoliang, Liu, Hong, Li, Wenhao +3 · 1 citation
    #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences
  6. Edge-guided Representation Learning for Underwater Object Detection
    2023/06/01 by Dai, Linhui, Liu, Hong, Song, Pinhao +3 · 1 citation
    #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences
  7. Explore Human Parsing Modality for Action Recognition
    2024/01/04 by Liu, Jinfu, Ding, Runwei, Wen, Yuhang +4 · 1 citation
    #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences