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(*: corresponding author, underlined: supervised student)

2024

  • Qing Zhong, G. Ding and Angela Yao,
    “OnlineTAS: An Online Baseline for Temporal Action Segmentation,”
    Neural Information Processing Systems, (NeurIPS), Vancouver, Canada, 2024.
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  • G. Ding, F. Sener, S. Ma and A. Yao,
    “Ordering Mistake Detection in Assembly Tasks,”
    Computer Vision and Pattern Recognition Workshop, (CVPRW), Seattle, US, 2024.
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  • G. Ding, H. Golong and A. Yao,
    “Coherent Temporal Synthesis for Incremental Action Segmentation,”
    Computer Vision and Pattern Recognition, (CVPR), Seattle, US, 2024.
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2023

  • G. Ding, F. Sener and A. Yao,
    “Temporal Action Segmentation: An Analysis of Modern Techniques,”
    IEEE Transactions on Pattern Analysis and Machine Intelligence, (TPAMI), IEEE, 2023.
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2022

  • G. Ding and A. Yao,
    “Temporal Action Segmentation with High-level Complex Activity Labels,”
    IEEE Transcations on Multimedia, (TMM), IEEE, 2022.
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  • G. Ding and A. Yao,
    “Leveraging Action Affinity and Continuity for Semi-supervised Temporal Action Segmentation,”
    European Conference on Computer Vision, (ECCV), Tel Aviv, Isreal, 2022.
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2021 and before

  • G. Ding*, S. Zhang, S. Khan, Z. Tang, J. Zhang and F. Porikli,
    “Feature Affinity based Pseudo Labeling for Semi-supervised Person Re-identification,”
    IEEE Transcations on Multimedia, (TMM), IEEE, 2019.
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  • G. Ding*, S. Khan, Z. Tang, and F. Porikli,
    “Feature Mask Network for Person Re-identification,”
    Pattern Recognition Letters, (PRL), Springer, 2019.
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  • G. Ding, S. Khan, and Z. Tang,
    “Dispersion-based Clustering for Unsupervised Person Re-identiļ¬cation,”
    British Machine Vision Conference, (BMVC), Cardiff, UK, 2019.
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  • G. Ding*, S. Zhang, S. Khan, and Z. Tang,
    “Center based Pseudo-labeling for Semi-supervised Person Re-identification,”
    International Conference of Multimedia and Expo Workshops, (ICMEW), San Diego, US, 2018.
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Arxived

  • G. Ding*, S. Khan, Z. Tang, J. Zhang and F. Porikli,
    “Towards better Validity: Dispersion based Clustering for Unsupervised Person Re-identification,”
    Arxiv paper 2019.
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