Yu Liu
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
UniFormer: Unified Transformer for Efficient Spatial-Temporal Representation Learning, Code
Kunchang Li, Yali Wang, Peng Gao, Guanglu Song, Yu Liu, Hongsheng Li, Yu Qiao
ICLR 2022
Switchable K-class Hyperplanes for Noise-robust Representation Learning
Boxiao Liu, Guanglu Song, Manyuan Zhang, Haihang You, Yu Liu+
2021 International Conference on Computer Vision (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 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Discriminability Distillation in Group Representation Learning
Manyuan Zhang, Guanglu Song, Hang Zhou, Yu Liu+
2020 European Conference on Computer Vision (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 European Conference on Computer Vision (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 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Revisiting the Sibling Head in Object Detector
Guanglu Song, Yu Liu+, Xiaogang Wang
(OpenImage 2019 Champion) 2020 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Rotate-and-Render: Unsupervised Photorealistic Face Rotation from Single-View Images
Hang Zhou, Jihao Liu, Ziwei Liu, Yu Liu+, Xiaogang Wang
2020 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
KPNet: Towards Minimal Face Detector
Guanglu Song, Yu Liu+, Yuhang Zang, Xiaogang Wang, Biao Leng, Qingsheng Yuan
(Oral) 2020 AAAI Conference on Artificial Intelligence (AAAI)
Temporal Interlacing Network
Hao Shao, Shengju Qian, Yu Liu+
2020 AAAI Conference on Artificial Intelligence (AAAI)
Differentiable Kernel Evolution
Yu Liu, Jihao Liu, Ailing Zeng, Xiaogang Wang
2019 IEEE International Conference on Computer Vision (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 Conference on Artificial Intelligence (AAAI)
Conditional Adversarial Generative Flow for Controllable Image Synthesis
Rui Liu, Yu Liu, Xinyu Gong, Xiaogang Wang, Hongsheng Li
2019 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Exploring Disentangled Feature Representation Beyond Face Identification
Yu Liu, Fangyin Wei, Jing Shao, Lv Sheng, Junjie Yan, Xiaogang Wang
2018 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Transductive Centroid Projection for Semi-supervised Large-scale Recognition
Yu Liu, Guanglu Song, Jing Shao, Xiao Jin, Xiaogang Wang
2018 European Conference on Computer Vision (ECCV)
Rethinking Feature Discrimination and Polymerization for Large-scale Recognition
Yu Liu, Hongyang Li, Xiaogang Wang
2017 Conference on Neural Information Processing Systems (NIPS) deep learning workshop
Recurrent Scale Approximation for Object Detection in CNN, Code
Yu Liu, Hongyang Li, Junjie Yan et al.
2017 IEEE International Conference on Computer Vision (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 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Quality Aware Network for Set to Set Recognition, Code
Yu Liu, Junjie Yan, Wanli Ouyang
2017 IEEE Conference on Computer Vision and Pattern Recognition (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 International Conference on Computer Vision (ICCV)
Correlation Congruence for Knowledge Distillation
Baoyun Peng, Xiao Jin, Jiaheng Liu, Shunfeng Zhou, Yichao Wu, Yu Liu, Dongsheng Li, Zhaoning Zhang
2019 IEEE International Conference on Computer Vision (ICCV)
Talking Face Generation by Adversarially Disentangled Audio-Visual Representation, Code
Hang Zhou, Yu Liu, Ziwei Liu, Ping Luo, Xiaogang Wang
(Oral) 2019 AAAI Conference on Artificial Intelligence (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 International Journal of Computer Vision (IJCV)
Region-based Quality Estimation Network for Large-Scale Person Re-identification
Guanglu Song, Biao Leng, Yu Liu, Congrui Hetang, Shaofan Cai<
2018 AAAI Conference on Artificial Intelligence (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 IEEE Conference on Computer Vision and Pattern Recognition (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 European Conference on Computer Vision (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, ...
IEEE Transactions on Pattern Analysis and Machine Intelligence (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
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