Long Chen

Postdoctoral Research Scientist
Digital Video and Multimedia (DVMM) Lab
Fu Foundation School of Engineering and Applied Science
Columbia University
Email (zjuchenlong A~T gmail.com)
[Résumé] [WeChat]

Long Chen is a postdoctoral research scientist at DVMM Lab, Columbia University in the City of New York working with Prof. Shih-Fu Chang (2021 - present). He obtained his Ph.D. degree in Computer Science from Zhejiang University and his Ph.D. advisor is Prof. Jun Xiao (2015 - 2020). During his Ph.D. period, he also worked closely with Prof. Hanwang Zhang from Nanyang Technological University and Prof. Tat-Seng Chua from National University of Singapore. He obtained his B.Eng. degree in Electronic Information Engineering from Dalian University of Technology (2011 - 2015). He was a senior research scientist at Tencent AI Lab (Shenzhen) working with Dr. Wei Liu (2020 - 2021).

Research Interest

His primary research interests are Computer Vision, Machine Learning, and Multimedia. Specifically, he aims to build an efficient vision system that can understand complex visual scenes as humans. By “human-like”, we mean that the vision systems should be equipped with three types of abilities:

1) Explainable: The model should rely on (right) explicit evidences when making decisions, ie, right for the right reasons.
Related Work: SCA-CNN (CVPR’17), CMAT (ICCV’19 Oral), SituFormer (AAAI’22), BIG (CVPR’22)

2) Robust: The model should be robust to some situations with only low-quality training data (eg, training samples are biased, noisy, or limited).
Related Work: CSS (CVPR’20), KDDAug (ECCV’22), NICE (CVPR’22 Oral), SP-AEN (CVPR’18), FCT (CVPR’22 Oral)

3) Universal: The model design is relatively universal, ie, it is expected to be effective for various tasks.
Related Work: CrossFormer (ICLR’22), GTR (EMNLP’21 Oral)

Selected Publications

  1. arXiv
    NICEST: Noisy Label Correction and Training for Robust Scene Graph Generation
    Lin Li, Long Chen, Hanrong Shi, Hanwang Zhang, Yi Yang, Wei Liu, and Jun Xiao
    arXiv preprint (arXiv) , arXiv , extension of CVPR’22 work
  2. arXiv
    Counterfactual Samples Synthesizing and Training for Robust Visual Question Answering
    Long Chen, Yuhang Zheng, Yulei Niu, Hanwang Zhang, and Jun Xiao
    arXiv preprint (arXiv) , arXiv , extension of CVPR’20 work
  3. ECCV
    Explicit Image Caption Editing
    Zhen Wang, Long Chen, Wenbo Ma, Guangxing Han, Yulei Niu, Jian Shao, and Jun Xiao
    European Conference on Computer Vision (ECCV) , 2022 , Codes
  4. ECCV
    Rethinking Data Augmentation for Robust Visual Question Answering
    Long Chen, Yuhang Zheng, and Jun Xiao
    European Conference on Computer Vision (ECCV) , 2022 , Codes
  5. CVPR
    Few-Shot Object Detection with Fully Cross-Transformer
    Guangxing Han, Jiawei Ma, Shiyuan Huang, Long Chen, and Shih-Fu Chang
    Computer Vision and Pattern Recognition (CVPR) , 2022 , Oral presentation
  6. CVPR
    The Devil is in the Labels: Noisy Label Correction for Robust Scene Graph Generation
    Lin Li, Long Chen, Yifeng Huang, Zhimeng Zhang, Songyang Zhang, and Jun Xiao
    Computer Vision and Pattern Recognition (CVPR) , 2022 , Codes , Oral presentation
  7. CVPR
    Classification-Then-Grounding: Reformulating Video Scene Graphs as Temporal Bipartite Graphs
    Kaifeng Gao, Long Chen, Yulei Niu, Jian Shao, and Jun Xiao
    Computer Vision and Pattern Recognition (CVPR) , 2022 , Codes
  8. ICLR
    CrossFormer: A Versatile Vision Transformer Hinging on Cross-scale Attention
    Wenxiao Wang, Lu Yao, Long Chen, Binbin Lin, Deng Cai, Xiaofei He, and Wei Liu
    International Conference on Learning Representations (ICLR) , 2022 , Codes
  9. EMNLP
    On Pursuit of Designing Multi-Modal Transformer for Video Grounding
    Meng Cao, Long Chen, Mike Zheng Shou, Can Zhang, and Yuexian Zou
    Empirical Methods in Natural Language Processing (EMNLP) , 2021 , Codes , Oral presentation
  10. EMNLP
    Natural Language Video Localization with Learnable Moment Proposals
    Shaoning Xiao, Long Chen, Jian Shao, Yueting Zhuang, and Jun Xiao
    Empirical Methods in Natural Language Processing (EMNLP) , 2021 , Codes
  11. CVPR
    Human-like Controllable Image Captioning with Verb-specific Semantic Roles
    Long Chen, Zhihong Jiang, Jun Xiao, and Wei Liu
    Computer Vision and Pattern Recognition (CVPR) , 2021 , Codes
  12. CVPR
    Counterfactual Samples Synthesizing for Robust Visual Question Answering
    Long Chen, Xin Yan, Jun Xiao, Hanwang Zhang, Shiliang Pu, and Yueting Zhuang
    Computer Vision and Pattern Recognition (CVPR) , 2020 , Codes
  13. EMNLP
    DEBUG: A Dense Bottom-Up Grounding Approach for Natural Language Video Localization
    Chujie Lu, Long Chen, Chilie Tan, Xiaolin Li, and Jun Xiao
    Empirical Methods in Natural Language Processing (EMNLP) , 2019 , Oral presentation
  14. ICCV
    Counterfactual Critic Multi-Agent Training for Scene Graph Generation
    Long Chen, Hanwang Zhang, Jun Xiao, Xiangnan He, Shiliang Pu, and Shih-Fu Chang
    International Conference on Computer Vision (ICCV) , 2019 , Oral presentation
  15. CVPR
    Zero-Shot Visual Recognition Using Semantics-Preserving Adversarial Embedding Networks
    Long Chen, Hanwang Zhang, Jun Xiao, Wei Liu, and Shih-Fu Chang
    Computer Vision and Pattern Recognition (CVPR) , 2018 , Codes
  16. CVPR
    SCA-CNN: Spatial and Channel-wise Attention in Convolutional Networks for Image Captioning
    Long Chen, Hanwang Zhang, Jun Xiao, Liqiang Nie, Jian Shao, Wei Liu, and Tat-Seng Chua
    Computer Vision and Pattern Recognition (CVPR) , 2017 , Codes , Google citations over 1000+ times
    Top-100 Most Cited Paper within 5 Years in CVPR, Google Scholar 2021&2022