Yu Liu's academic page

Yu Liu's academic page 

General Manager & Executive Director, SenseTime
PI, Shanghai AI Lab
Industrial doctoral supervisor, SJTU
liuyuisanai@gmail.com

Google Scholar

News

  • Job positions and PhD program are open for talents interested in AIGC, super HUGE model for NLP and CV and Game AI.

  • [2023] Our OpenDILab achieves 10,000+ stars on GitHub!

  • [2023] We release our AIGC service MiaoHua, have a try!

  • [2023] My team have 20 papers published on TPAMI/ICCV/ICLR/NeurIPS/IROS/AAAI in 2023

  • [2023] My team won the championship of CARLA Autonomous Driving Challenge

  • [2022] My team have 9 papers published on ECCV/CoRL/NeurIPS/AAAI in 2022

  • [2022] We release DI-Star, an implementation of AlphaStar in pyTorch, beating pro players with 6000+ MMR.

  • [2021] My team won the best paper of ICCV21 MFR workshop

  • [2021] My team won 3 championships of ICCV21 The Masked Face Recognition Challenge

  • [2021] We release OpenDILab, an open source decision intelligence platform

  • [2020] 5 papers with 1 oral got published on CVPR/ECCV 2020

  • [2020] My team won 2 championships of ActivityNet on the Spatio-temporal Action Localization (AVA) track and the Trimmed Activity Recognition (Kinetics) track

  • [2020] My team won the championship of NIST FRVT 1:N, a 12-million-level commercial facial recognition benchmark held by US government.

  • [2019] 7 papers with 4 oral presentations published on ICCV/CVPR/AAAI in 2019

  • [2019] I won 4 champions in 4 ICCV AI challenges:MMIT (solutions), OpenImage Instance Segmentation Challenge (solutions), OpenImage Object Detection Challenge (solutions), LFR 2019 (model and report)

  • [2019] I was granted the Google PhD Fellowship 2019.

  • [2018] 4 papers published by CVPR/ECCV/IJCV/AAAI in 2018.

  • [2017] 6 papers published on CVPR/ICCV/NIPS/AAAI/T-PAMI in 2017.

  • [2016] We win the 1st place in ECCV-MOT16 Challenge! code

  • [2016] We win the 1st place in ImageNet Challenge 2016! code

About me

I am currently the Executive Director of Research in SenseTime Group, and the GM of ADG Business Unit, in charge of the research, productization, and business of HUGE neural models, with a particular focus on large-scale AIGC and multi-modal models. Previously I obtain my PhD from MMLab, CUHK, supervised by Prof. Xiaogang Wang.
When I was young, I devoted myself to various cutting-edge AI research problems and published dozens of papers in top-tier conferences. However, with a deeper understanding of technology, I am now more focused on tackling problems that can truly advance the field and make AI serve all of humanity. Therefore, since 2020, I have not been concerned with the quantity of "research papers", and have instead formed a team of over 100 researchers and product developers. With over 4,000 GPUs at our disposal, we are committed to creating top-notch technology and products based on super HUGE NLP and CV models that can serve the public. Contact me if you are interested.

Working Experience

Publications

See full list at Google Scholar.
*equal contribition +corresponding author

Projects & Datasets

GitHub

  • OpenDILab, a generalized Decision Intelligence engine.

  • X-Temporal, Easily implement SOTA video understanding methods with PyTorch on multiple machines and GPUs

  • CaffeMex v2.3, a multi-GPU & memory-reduced MAT-Caffe on LINUX and WINDOWS

  • Labeled Pedestrains in the Wild ,a large scale pedestrain re-identification benchmark