Shilong Liu Homepage

Hi! This is Shilong Liu, 刘世隆 in Chinese. I’m a ceil(now() - 2020.9)th year Ph.D. candidate at the Department of Computer Science and Technology, Tsinghua University, under the supervision of Prof. Lei Zhang, Prof. Hang Su, and Prof. Jun Zhu. I got my bachelor’s degree from the Department of Industrial Engineering, Tsinghua University in 2020.

I am an intern of computer vision at International Digital Economy Academy (IDEA), under the supervision of Prof. Lei Zhang.

I was a summer intern at Microsoft Research, Redmond in June to Septemeber 2023, under the supervision of Dr. Chunyuan Li and Dr. Hao Cheng. I have a close cooperation with Dr. Jianwei Yang as well.

My research interest includes computer vision, object detection, and multi-modal learning.

Contact me with my email: slongliu86 AT gmail.com or liusl20 AT mails.tsinghua.edu.cn

News

Nov 5, 2023	I was awarded as the CCF-CV Rising Star Scholar 2023 (CCF-CV 学术新锐学者, 3 people per year)! Thanks to the China Computer Federation, Computer Vision Committee.
Mar 13, 2023	We release a strong open-set object detection model Grounding DINO that achieves the best results on open-set object detection tasks. It achieves 52.5 zero-shot AP on COCO detection, without any COCO training data! It achieves 63.0 AP on COCO after fine-tuning. Code and checkpoints will be available here.
Sep 22, 2022	We release a toolbox detrex that provides state-of-the-art Transformer-based detection algorithms. It includes DINO with better performance. Welcome to use it!

Selected Publications

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!

arXiv Bib Code

@article{liu2023grounding,
  title = {Grounding dino: Marrying dino with grounded pre-training for open-set object detection},
  author = {Liu, Shilong and Zeng, Zhaoyang and Ren, Tianhe and Li, Feng and Zhang, Hao and Yang, Jie and Li, Chunyuan and Yang, Jianwei and Su, Hang and Zhu, Jun and others},
  journal = {arXiv preprint arXiv:2303.05499},
  year = {2023},
}

DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection

Hao Zhang*, Feng Li*, Shilong Liu*, and 5 more authors

2023

The first DETR-based object detector that achieved 1st on the COCO detection leaderboard.

arXiv Bib Code

@misc{zhang2022dino,
  title = {DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection},
  author = {Zhang*, Hao and Li*, Feng and Liu*, Shilong and Zhang, Lei and Su, Hang and Zhu, Jun and Ni, Lionel M. and Shum, Heung-Yeung},
  booktitle = {International Conference on Learning Representations},
  year = {2023},
}

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.

arXiv Bib Code

@inproceedings{liu2022dabdetr,
  title = {{DAB}-{DETR}: Dynamic Anchor Boxes are Better Queries for {DETR}},
  author = {Liu, Shilong and Li, Feng and Zhang, Hao and Yang, Xiao and Qi, Xianbiao and Su, Hang and Zhu, Jun and Zhang, Lei},
  booktitle = {International Conference on Learning Representations},
  year = {2022},
  url = {https://openreview.net/forum?id=oMI9PjOb9Jl},
}

Query2Label: A Simple Transformer Way to Multi-Label Classification

Shilong Liu, Lei Zhang, Xiao Yang, and 2 more authors

2021

A novel transformer-based multi-label classification model, achieving SOTA on four benchmarks.

arXiv Bib Code

@misc{liu2021query2label,
  title = {Query2Label: A Simple Transformer Way to Multi-Label Classification},
  author = {Liu, Shilong and Zhang, Lei and Yang, Xiao and Su, Hang and Zhu, Jun},
  year = {2021},
  eprint = {2107.10834},
  archiveprefix = {arXiv},
  primaryclass = {cs.CV},
}