Yu Liu

Yu Liu 

General Manager of Game BU & Research Director, SenseTime
PI, Shanghai AI Lab
PhD @ Multimedia Lab, CUHK

liuyuisanai@gmail.com

Google Scholar
Resume
GitHub

News

  • Job positions and PhD program are open for talents interested in deep RL, super HUGE neural architecture, AutoML and Game AI.

  • [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] 2 papers got accepted on 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.

  • [2020] 3 papers with 1 oral got accepted on CVPR 2020

  • [2019] 7 papers with 4 oral presentations accepted 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 accepted by CVPR/ECCV/IJCV/AAAI in 2018.

  • [2017] 6 papers accepted 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 GM of AI-Game Business Unit and research director in SenseTime Group, leading a team with 100+ members, and also a Principal Investigator in Shanghai AI Lab.

Before that, I obtain my PhD from Multimedia Lab (MMLab), the Chinese University of Hong Kong, supervised by Prof. Xiaogang Wang. I'm the only awardee of Google PhD Fellowship 2019 in the Greater China area.

My research interests include: Artificial General Intelligence, Deep RL and neural network understanding under billions of data. Previously I was also proficient in basic computer vision topics (detection, classification, recognition, generation, synthesis and video understanding).

In recent years I am a reviewer for CVPR, ICCV, NeurIPS, ICLR, AAAI, IJCAI, T-PAMI, IJCV, TCSVT, TIP, PRCV.

Working Experience

  • (part-time) PI at Shanghai AI Lab.
    In charge of the Decision Intelligence team and especially the "OpenDILab" open-soursed platform.

  • GM of AI-Game BU & Research director, SenseTime. (since Oct. 2019)
    Leading 3 research departments: X-Lab, Decision Intelligence and Fundamental Model.

  • Research intern at Google Research, Seattle. (Jun 2019 to Oct 2019)
    Worked on neural network understanding and NAS with Research Scientists Xuhui Jia, Mingxing Tan and Raviteja Vemulapalli.

  • Research intern & part-time researcher consultant at SenseTime Research. (Jan 2016 to Jan 2019)
    Worked on large-scale face analysis (detection, recognition, synthesis), generative model and neural network miniaturizing.

  • Research intern at Microsoft Research (Asia), Visual Computing Group. (2015 to 2016)
    Worked on object detection and recognition with Dr. Dong Chen.

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