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

• 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.

	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

• Winner at the ImageNet LSVRC 2017 Image Classification (CVPR17 Workshop).
• Winner at the ImageNet LSVRC 2015 Scene Classification (ICCV15 Workshop).

Last Update: March 28, 2023

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