Li Shen (申丽)

lshen.lsh@gmail.com

I am an experienced Staff Researcher with a strong background in artificial intelligence and computer vision. Currently, I work at Alibaba Damo Academy, where I conduct research to tackle 3D-aware representation learning and develop innovative solutions for 3D scene reconstruction and synthesis in VR/AR applications. Prior to joining Alibaba, I held a Senior Researcher position at Tencent AI Lab. Before my tenure at Tencent, I was a researcher in the Visual Geometry Group (VGG) at the University of Oxford, where I worked with Prof. Andrew Zisserman.

I received my PhD in Computer Science from the University of Chinese Academy of Sciences, under the supervision of Prof. Qingming Huang. I was also supervised by Prof. Zhouchen Lin at Peking University.
My research interests are in computer vision and deep learning.

Google Scholar

News

  • We are organising Neural Architects Workshop at ICCV 2019.

    Neural Architects: What have we learned and where are we going? - for all things related to Deep Neural Network design.
    Call for papers and additional info can be found here.


Research

Compressing Volumetric Radiance Fields to 1 MB
Lingzhi Li, Zhen Shen, Zhongshu Wang, Li Shen and Liefeng Bo
Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
Paper / ArXiv / Code / Bibtex
Streaming Radiance Fields for 3D Video Synthesis
Lingzhi Li, Zhen Shen, Zhongshu Wang, Li Shen and Ping Tan
Advances in Neural Information Processing Systems (NeurIPS), 2022.
Paper / ArXiv / Code / Bibtex
Depth-Aware Generative Adversarial Network for Talking Head Video Generation
Fa-Ting Hong, Longhao Zhang, Li Shen and Dan Xu
Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
Paper / ArXiv / Code / Bibtex
Learning Meta Representations for Agents in Multi-Agent Reinforcement Learning
Shenao Zhang, Li Shen, Lei Han and Li Shen
Gamification and Multiagent Solutions Workshop, ICLR, 2022.
Paper / ArXiv / Bibtex
Structure-Regularized Attention for Deformable Object Representation
Shenao Zhang, Li Shen, Zhifeng Li and Wei Liu
Object Representations for Learning and Reasoning Workshop, NeurIPS, 2020.
Paper / ArXiv / Code / Bibtex
AlphaGAN: Fully Differentiable Architecture Search for Generative Adversarial Networks
Yuesong Tian, Li Shen Li Shen, Guinan Su, Zhifeng Li and Wei Liu
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021.
Paper / ArXiv / Code / Bibtex
Milenas: Efficient neural architecture search via mixed-level reformulation
Chaoyang He, Haishan Ye, Li Shen, and Tong Zhang
Conference on Computer Vision and Pattern Recognition (CVPR), 2020.
Paper / ArXiv / Code / Bibtex
Squeeze-and-Excitation Networks
Jie Hu, Li Shen, Samuel Albanie, Gang Sun, and Enhua Wu
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2019.
This paper is an extension of prior work SENets.
Paper / ArXiv / Code & Model / Bibtex
Gather-Excite: Exploiting Feature Context in Convolutional Neural Networks
Jie Hu*, Li Shen*, Samuel Albanie*, Gang Sun, and Andrea Vedaldi
Advances in Neural Information Processing Systems (NeurIPS), 2018.
Paper / ArXiv / Code & Model / Bibtex
Comparator Networks
Weidi Xie, Li Shen, and Andrew Zisserman
European Conference on Computer Vision (ECCV), 2018.
Paper / ArXiv / Bibtex
Squeeze-and-Excitation Networks
Jie Hu*, Li Shen*, and Gang Sun
Conference on Computer Vision and Pattern Recognition (CVPR), 2018 (Oral).
Winner at the ILSVRC 2017 Image Classification.
Paper / Code & Model / Bibtex
Vggface2: A dataset for recognising faces across pose and age
Qiong Cao, Li Shen, Weidi Xie, Omkar M. Parkhi, and Andrew Zisserman
Conference on Automatic Face & Gesture Recognition (FG), 2018 (Oral).
Paper / ArXiv / Code & Model / Project / Bibtex
Relay Backpropagation for Effective Learning of Deep Convolutional Neural Networks
Li Shen, Zhouchen Lin, and Qingming Huang
European conference on computer vision (ECCV), 2016.
Winner at the ILSVRC 2015 Scene Classification.
Paper / ArXiv / Model / Bibtex
Co-occurrence Feature Learning for Skeleton Based Action Recognition Using Regularized Deep LSTM Networks
Wentao Zhu, Cuiling Lan, Junliang Xing, Wenjun Zeng, Yanghao Li, Li Shen, and Xiaohui Xie
Thirtieth AAAI Conference on Artificial Intelligence (AAAI), 2016.
Paper / ArXiv / Bibtex
Multi-Level Discriminative Dictionary Learning with Application to Large Scale Image Classification
Li Shen, Gang Sun, Qingming Huang, Shuhui Wang, Zhouchen Lin, and Enhua Wu
IEEE Transactions on Image Processing, 2015.
Paper / Bibtex
Adaptive Sharing for Image Classification
Li Shen, Gang Sun, Zhouchen Lin, Qingming Huang, and Enhua Wu
International Joint Conference on Artificial Intelligence (IJCAI), 2015.
Paper / Bibtex
Multi-Level Discriminative Dictionary Learning towards Hierarchical Visual Categorization
Li Shen, Shuhui Wang, Gang Sun, Shuqiang Jiang, and Qingming Huang
Conference on Computer Vision and Pattern Recognition (CVPR), 2013.
Paper / Bibtex


Academic Competitions




Last Update: March 28, 2023

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