MMLab@NTU was formed on the 1 August 2018, with a research focus on computer vision and deep learning. Its sister lab is MMLab@CUHK. It is now a group with four faculty members and more than 25 members including research fellows, research assistants, and PhD students.
Members in MMLab@NTU conduct research primarily in low-level vision, image and video understanding, creative content creation, 3D scene understanding and reconstruction. Have a look at the overview of our research. All publications are listed here.
Three Champions in NTIRE 2021 Challenge
04/2021: NTIRE is the most competitive challenge for low-level vision tasks. With BasicVSR++, we won three Champions in the tracks for video super-resolution and quality enhancement of heavily compressed videos. Congrats to the team!
03/2021: The team has a total of 18 papers accepted to CVPR 2021 (including four orals).
Best PKL Award in nuScenes Detection Challenge
12/2020: In the recent nuScenes 3D detection challenge of the 5th AI Driving Olympics in NeurIPS 2020, we obtained the best PKL award and the second runner-up by multi-modality entry, and the best vision-only results!
07/2020: Eight papers to appear in ECCV 2020 (with one oral and one spotlight).
News and Highlights
- 05/2021: Five outstanding CVPR 2021 reviewers from our team! Congrats to Chongyi Li, Davide Moltisanti, Xiangyu Xu, Liang Pan, and Jiahao Xie.
- 01/2021: Two papers to appear in ICLR 2021.
- 12/2020: Shangchen Zhou is recognized as one the top 10% outstanding reviewers in NeurIPS 2020.
- 07/2020: New toolboxes such as MMEditing, MMDetection3D and OpenSelfSup are released under OpenMMLab.
- 03/2020: Nine papers to appear in CVPR 2020 (including one oral).
- 10/2019: Our MMLab-SelfSup team won all four tracks in the Facebook AI Self-Supervision Challenge.
- 10/2019: Our MMDet team won the COCO 2019 Object Detection Challenge (without external data). We release the codebase MMDetection at OpenMMLab.