Yu Liu

General Manager & Senior Director, SenseTime PI, Shanghai AI Lab Industrial doctoral supervisor, SJTU 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, AIGC and Game AI.

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

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

• [2023] My team have 2 papers published on ICLR/AAAI in 2023

• [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 GM of ADG Business Unit and a senior director of research 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.
  - Lead of the Decision Intelligence team and especially the "OpenDILab" open-soursed platform.

• GM of ADG BU & Senior Research director, SenseTime. (since Oct. 2019)
  - General Manager of AI Decision and Game Business Unit.
  - Direcotr of 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

• GoBigger: A Scalable Platform for Cooperative-Competitive Multi-Agent Interactive Simulation, Project, Challenge
  Ming Zhang, Shenghan Zhang, Zhenjie Yang, Lekai Chen, Jinliang Zheng, Chao Yang, Chuming Li, Hang Zhou, Yazhe Niu, Yu Liu⁺
  2023 ICLR

• Cooperative Multi-agent Q-learning with Bidirectional Action-Dependency
  Chuming Li, Jie Liu, Yinmin Zhang, Yuhong Wei, Yazhe Niu, Yaodong Yang, Yu Liu⁺, Wanli Ouyang
  2023 AAAI

• Large-batch Optimization for Dense Visual Predictions, Code
  Zeyue Xue, Jianming Liang, Guanglu Song, Zhuofan Zong, Liang Chen, Yu Liu⁺, Ping Luo⁺
  2022 NeurIPS

• Safety-Enhanced Autonomous Driving Using Interpretable Sensor Fusion Transformer
  Hao Shao, Letian Wang, Ruobing Chen, Hongsheng Li, Yu Liu⁺
  2022 CoRL

• UniNet: Unified Architecture Search with Convolution, Transformer, and MLP
  Jihao Liu, Xin Huang, Guanglu Song, Hongsheng Li⁺, Yu Liu⁺
  2022 ECCV

• Self-slimmed Vision Transformer
  Zhuofan Zong, Kunchang Li, Guanglu Song, Yali Wang, Yu Qiao, Biao Leng, Yu Liu⁺
  2022 ECCV

• TokenMix: Rethinking Image Mixing for Data Augmentation in Vision Transformers
  Jihao Liu, Boxiao Liu, Hang Zhou, Hongsheng Li⁺, Yu Liu⁺
  2022 ECCV

• Unifying Visual Perception by Dispersible Points Learning
  Jianming Liang, Guanglu Song, Biao Leng, Yu Liu⁺
  2022 ECCV

• Towards Robust Face Recognition with Comprehensive Search
  Manyuan Zhang, Guanglu Song, Yu Liu⁺, Hongsheng Li
  2022 ECCV

• Rethinking Robust Representation Learning Under Fine-grained Noisy Faces
  Bingqi Ma, Guanglu Song, Boxiao Liu, Yu Liu⁺
  2022 ECCV

• UniFormer: Unified Transformer for Efficient Spatial-Temporal Representation Learning, Code
  Kunchang Li, Yali Wang, Peng Gao, Guanglu Song, Yu Liu, Hongsheng Li, Yu Qiao
  2022 ICLR

• Switchable K-class Hyperplanes for Noise-robust Representation Learning
  Boxiao Liu, Guanglu Song, Manyuan Zhang, Haihang You, Yu Liu⁺
  2021 ICCV

• Actor-Context-Actor Relation Network for Spatio-Temporal Action Localization
  Junting Pan, Siyu Chen, Mike Zheng Shou, Yu Liu, Jing Shao, Hongsheng Li
  2021 CVPR

• Discriminability Distillation in Group Representation Learning
  Manyuan Zhang, Guanglu Song, Hang Zhou, Yu Liu⁺
  2020 ECCV

• Learning Where to Focus for Efficient Video Object Detection
  Zhengkai Jiang, Yu Liu⁺, Ceyuan Yang, Jihao Liu, Gao Peng, Qian Zhang, Shiming Xiang, Chunhong Pan
  2020 ECCV

• Search to Distill: Pearls are Everywhere but not the Eyes
  Yu Liu, Xuhui Jia, Mingxing Tan, Raviteja Vemulapalli, Yukun Zhu, Bradley Green, Xiaogang Wang
  (Oral) 2020 CVPR

• Revisiting the Sibling Head in Object Detector
  Guanglu Song, Yu Liu⁺, Xiaogang Wang
  (OpenImage 2019 Champion) 2020 CVPR

• Rotate-and-Render: Unsupervised Photorealistic Face Rotation from Single-View Images
  Hang Zhou, Jihao Liu, Ziwei Liu, Yu Liu⁺, Xiaogang Wang
  2020 CVPR

• KPNet: Towards Minimal Face Detector
  Guanglu Song, Yu Liu⁺, Yuhang Zang, Xiaogang Wang, Biao Leng, Qingsheng Yuan
  (Oral) 2020 AAAI

• Temporal Interlacing Network
  Hao Shao, Shengju Qian, Yu Liu⁺
  2020 AAAI

• Differentiable Kernel Evolution
  Yu Liu, Jihao Liu, Ailing Zeng, Xiaogang Wang
  2019 IEEE ICCV

• Towards Flops-constrained Face Recognition, Code
  Yu Liu*, Guanglu Song*, Manyuan Zhang*, Jihao Liu*, Yucong Zhou, Junjie Yan
  (Top-1 Solution) 2019 ICCV Lightweight Face Recognition Challenge & Workshop

• Gradient Harmonized Single-stage Detector,Code
  Buyu Li*, Yu Liu*, Xiaogang Wang
  (Oral) 2019 AAAI

• Conditional Adversarial Generative Flow for Controllable Image Synthesis
  Rui Liu, Yu Liu, Xinyu Gong, Xiaogang Wang, Hongsheng Li
  2019 CVPR

• Exploring Disentangled Feature Representation Beyond Face Identification
  Yu Liu, Fangyin Wei, Jing Shao, Lv Sheng, Junjie Yan, Xiaogang Wang
  2018 CVPR

• Transductive Centroid Projection for Semi-supervised Large-scale Recognition
  Yu Liu, Guanglu Song, Jing Shao, Xiao Jin, Xiaogang Wang
  2018 ECCV

• Rethinking Feature Discrimination and Polymerization for Large-scale Recognition
  Yu Liu, Hongyang Li, Xiaogang Wang
  2017 NIPS deep learning workshop

• Recurrent Scale Approximation for Object Detection in CNN, Code
  Yu Liu, Hongyang Li, Junjie Yan et al.
  2017 IEEE ICCV

• Beyond Trade-off: Accelerate FCN-based Face Detector with Higher Accuracy
  Guanglu Song*, Yu Liu*, Ming Jiang, Yujie Wang, Junjie Yan, Biao Leng
  2018 CVPR

• Quality Aware Network for Set to Set Recognition, Code
  Yu Liu, Junjie Yan, Wanli Ouyang
  2017 CVPR

• Knowledge Distillation via Route Constrained Optimization
  Xiao Jin, Baoyun Peng, Yichao Wu, Yu Liu, Jiaheng Liu, Ding Liang, Junjie Yan, Xiaolin Hu
  (Oral) 2019 IEEE ICCV

• Correlation Congruence for Knowledge Distillation
  Baoyun Peng, Xiao Jin, Jiaheng Liu, Shunfeng Zhou, Yichao Wu, Yu Liu, Dongsheng Li, Zhaoning Zhang
  2019 IEEE ICCV

• Talking Face Generation by Adversarially Disentangled Audio-Visual Representation, Code
  Hang Zhou, Yu Liu, Ziwei Liu, Ping Luo, Xiaogang Wang
  (Oral) 2019 AAAI

• Zoom Out-and-In Network with Map Attention Decision for Region Proposal and Object Detection, Code
  Hongyang Li, Yu Liu, W Ouyang, X Wang
  2018 IJCV

• Region-based Quality Estimation Network for Large-Scale Person Re-identification
  Guanglu Song, Biao Leng, Yu Liu, Congrui Hetang, Shaofan Cai
  2018 AAAI

• Learning Deep Features via Congenerous Cosine Loss for Person Recognition, Code
  Yu Liu, Hongyang Li, Xiaogang Wang
  arxiv:1702.06890, 2017

• Scale-Aware Face Detection
  Zekun Hao, Yu Liu, Hongwei Qin, Junjie Yan
  2017 CVPR

• POI: Multiple Object Tracking with High Performance Detection and Appearance Feature
  F Yu, W Li, Q Li, Y Liu, X Shi, J Yan
  (Top-1 Solution) 2016 ECCV workshop

• Crafting GBD-Net for Object Detection
  X Zeng, W Ouyang, J Yan, H Li, T Xiao, K Wang, Y Liu, Y Zhou, B Yang, ...
  T-PAMI

• 3D object understanding with 3D Convolutional Neural Networks
  B Leng, Y Liu, K Yu, X Zhang, Z Xiong
  Information Sciences 366, 188-201, 2016

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

Yu Liu