About Me

I’m a third-year PhD (2021-now) student at the Department of Computer Science & Engineering, Hong Kong University of Science and Technology, co-supervised by Prof. Heung-Yeung Shum and Prof. Lionel M. Ni. I interned at International Digital Economy Academy, Shenzhen (advised by Prof. Lei Zhang) and Microsoft Research, Redmond (advised by Dr. Jianwei Yang and Dr. Chunyuan Li). Previously, I obtained my bachelor’s degree from Computer Science and Technology, South China University of Science and Technology in 2021.

📌My research interests lie in visual understanding/generation and multi-modal learning.

✉️ Welcome to contact me for any discussion and cooperation!

🔥 News

📝 Recent Works

Refer to my google scholar for the full list.

  • Semantic-SAM: Segment and Recognize Anything at Any Granularity.
    Feng Li*, Hao Zhang*, Peize Sun, Xueyan Zou, Shilong Liu, Jianwei Yang, Chunyuan Li, Lei Zhang, Jianfeng Gao.
    arxiv 2023.
    [Paper][Code]

  • SEEM: Segment Everything Everywhere All at Once.
    Xueyan Zou*, Jianwei Yang*, Hao Zhang*, Feng Li*, Linjie Li, Jianfeng Gao, Yong Jae Lee.
    NeurIPS 2023.
    [Paper][Code]

  • Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection.
    Shilong Liu, Zhaoyang Zeng, Tianhe Ren, Feng Li, Hao Zhang, Jie Yang, Chunyuan Li, Jianwei Yang, Hang Su, Jun Zhu, Lei Zhang.
    arxiv 2023.
    [Paper][Code]

  • Lite DETR: An Interleaved Multi-Scale Encoder for Efficient DETR.
    Feng Li, Ailing Zeng, Shilong Liu, Hao Zhang, Lei Zhang, Lionel M. Ni.
    CVPR 2023.
    [Paper][Code]

  • Mask DINO: Towards A Unified Transformer-based Framework for Object Detection and Segmentation.
    Feng Li*, Hao Zhang*, Huaizhe Xu, Shilong Liu, Lei Zhang, Lionel M. Ni, Heung-Yeung Shum.
    CVPR 2023.
    [Paper][Code]

  • DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection.
    Hao Zhang*, Feng Li*, Shilong Liu*, Lei Zhang, Hang Su, Jun Zhu, Lionel M. Ni, Heung-Yeung Shum.
    ICLR 2023.
    [Paper][Code] Rank 2nd on ICLR 2023 Most Inflentical Papers

  • DN-DETR: Accelerate DETR Training by Introducing Query DeNoising.
    Feng Li*, Hao Zhang*, Shilong Liu, Jian Guo, Lionel M. Ni, Lei Zhang.
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2022. Oral presentation.
    [Paper][Code]

  • DAB-DETR: Dynamic Anchor Boxes are Better Queries for DETR.
    Shilong Liu, Feng Li, Hao Zhang, Xiao Yang, Xianbiao Qi, Hang Su, Jun Zhu, Lei Zhang.
    International Conference on Learning Representations (ICLR) 2022.
    [Paper][Code]

(* denotes equal contribution.)

🎖 Selected Awards

  • Hong Kong Postgraduate Scholoarship, 2021
  • Contemporary Undergraduate Mathematical Contest in Modeling(CUMCM), National first prize, 2019.

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