A full paper list is available at my google scholar page.


  1. groundingdino_pv.png
    Grounding dino: Marrying dino with grounded pre-training for open-set object detection
    Shilong Liu, Zhaoyang Zeng, Tianhe Ren, and 8 more authors
    arXiv preprint arXiv:2303.05499, 2023
    SOTA open-set object detector. 52.5AP on COCO without COCO training data!
  2. maskdino_pv.jpeg
    Mask DINO: Towards A Unified Transformer-based Framework for Object Detection and Segmentation
    Feng Li, Hao Zhang, Huaizhe Xu, and 4 more authors
    In , 2023
    SOTA object detection and segmentation model.
  3. dqdetr_pv.png
    DQ-DETR: Dual Query Detection Transformer for Phrase Extraction and Grounding
    Liu Shilong, Liang Yaoyuan, Huang Shijia, and 5 more authors
    In Proceedings of the AAAI Conference on Artificial Intelligence, 2023
    A comparison of object detection, REC, and phrase grounding tasks.
  4. dino_pv.png
    DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection
    Hao Zhang*, Feng Li*, Shilong Liu*, and 5 more authors
    The first DETR-based object detector that achieved 1st on the COCO detection leaderboard.


  1. dndetr_pv.png
    DN-DETR: Accelerate detr training by introducing query denoising
    Feng Li*, Hao Zhang*, Shilong Liu, and 3 more authors
    In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022
    A novel denoising training strategy for DETR, achieving faster convergence and better performance.
  2. dabdetr_pv.png
    DAB-DETR: Dynamic Anchor Boxes are Better Queries for DETR
    Shilong Liu, Feng Li, Hao Zhang, and 5 more authors
    In International Conference on Learning Representations, 2022
    A deep understanding of DETR’s query, and formulating queries as anchor boxes.


  1. q2l_pv.png
    Query2Label: A Simple Transformer Way to Multi-Label Classification
    Shilong Liu, Lei Zhang, Xiao Yang, and 2 more authors
    A novel transformer-based multi-label classification model, achieving SOTA on four benchmarks.