Bio

I am a Senior Researcher at Tencent Youtu Lab. My research interests lie in the area of computer vision and deep learning. Before joining Tencent, I recerived my M.S. degree from Xiamen University in 2018 under the supervision of Prof. Rongrong Ji. I received my B.S. degree from Zhengzhou University in 2015 under the supervision of Prof. Mingliang Xu.

Activities

• Reviewer for CVPR, ICCV, ECCV, AAAI, ICML, ICLR, and NeurIPS.

Selected Publications

Below are some of the works that represent my main research interests. Full paper list (including preprints) could be found at Google Scholar.

(* corresponding author)

	LocLoc: Low-level Cues and Local-area Guides for Weakly Supervised Object Localization Xinzi Cao, Xiawu Zheng, Yunhang Shen, Ke Li, Jie Chen, Yutong Lu, Yonghong Tian. ACM International Conference on Multimedia (ACM MM), 2023. Paper
	Masked Autoencoders are Efficient Class Incremental Learners Jiang-Tian Zhai, Xialei Liu, Andy Bagdanov, Ke Li, Ming-Ming Cheng. International Conference on Computer Vision (ICCV), 2023. Paper, Code
	MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models Chaoyou Fu, Peixian Chen, Yunhang Shen, Yulei Qin, Mengdan Zhang, Xu Lin, Zhenyu Qiu, Wei Lin, Jinrui Yang, Xiawu Zheng, Ke Li*, Xing Sun, Rongrong Ji. arxiv, 2023 Paper, Code
	A Survey on Multimodal Large Language Models Shukang Yin , Chaoyou Fu, Sirui Zhao, Ke Li, Xing Sun, Tong Xu, Enhong Chen. arxiv, 2023 Paper, Code
	CF-ViT: A General Coarse-to-Fine Method for Vision Transformer Mengzhao Chen, Mingbao Lin, Ke Li, Yunhang Shen, Yongjian Wu, Fei Chao, Rongrong Ji. Proceedings of the AAAI Conference on Artificial Intelligence (AAAI, Oral), 2023 Paper, Code
	Adaptive Hierarchy-Branch Fusion for Online Knowledge Distillation Linrui Gong, Shaohui Lin, Baochang Zhang, Yunhang Shen, Ke Li, Ruizhi Qiao, Bo Ren, Muqing Li, Zhou Yu, Lizhuang Ma. Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2023 Paper
	PyramidCLIP: Hierarchical Feature Alignment for Vision-language Model Pretraining Yuting Gao, Jinfeng Liu, Zihan Xu, Jun Zhang, Ke Li, Rongrong Ji, Chunhua Shen. Advances in Neural Information Processing Systems (NeurIPS, Oral), 2022 Paper, Code
	Learning Best Combination for Efficient N:M Sparsity Yuxin Zhang, Mingbao Lin, Zhihang Lin, Yiting Luo, Ke Li, Fei Chao, Yongjian Wu, Rongrong Ji. Advances in Neural Information Processing Systems (NeurIPS), 2022 Paper, Code
	Fine-grained Data Distribution Alignment for Post-Training Quantization Yunshan Zhong, Mingbao Lin, Mengzhao Chen, Ke Li, Yunhang Shen, Fei Chao, Yongjian Wu, Rongrong Ji. European Conference on Computer Vision (ECCV), 2022 Paper, Code
	Dynamic Dual Trainable Bounds for Ultra-low Precision Super-Resolution Networks Yunshan Zhong, Mingbao Lin, Xunchao Li, Ke Li, Yunhang Shen, Fei Chao, Yongjian Wu, Rongrong Ji. European Conference on Computer Vision (ECCV), 2022 Paper, Code
	Long-Tailed Class Incremental Learning Xialei Liu, Yusong Hu, Xu-Sheng Cao, Andy Bagdanov, Ke Li, Ming-Ming Cheng. European Conference on Computer Vision (ECCV), 2022 Paper, Code
	DisCo: Remedying Self-supervised Learning on Lightweight Models with Distilled Contrastive Learning Yuting Gao, Jia-Xin Zhuang, Shaohui Lin, Hao Cheng, Xing Sun, Ke Li*, Chunhua Shen. European Conference on Computer Vision (ECCV, Oral), 2022 Paper, Code
	Efficient Decoder-free Object Detection with Transformers Peixian Chen, Mengdan Zhang, Yunhang Shen, Kekai Sheng, Yuting Gao, Xing Sun, Ke Li*, Chunhua Shen. European Conference on Computer Vision (ECCV), 2022 Paper, Code
	ARM: Any-Time Super-Resolution Method Bohong Chen, Mingbao Lin, Kekai Sheng, Mengdan Zhang, Peixian Chen, Ke Li, Liujuan Cao, Rongrong Ji. European Conference on Computer Vision (ECCV), 2022 Paper, Code
	Self-supervised Models are Good Teaching Assistants for Vision Transformers Haiyan Wu, Yuting Gao, Yinqi Zhang, Shaohui Lin, Yuan Xie, Xing Sun, Ke Li . International Conference on Machine Learning (ICML), 2022 Paper
	Training-free Transformer Architecture Search Qinqin Zhou, Kekai Sheng, Xiawu Zheng, Ke Li, Xing Sun, Yonghong Tian, Jie Chen, Rongrong Ji . Computer Vision and Pattern Recognition (CVPR, Oral), 2022 Paper, Code
	Evo-ViT: Slow-Fast Token Evolution for Dynamic Vision Transformer Yifan Xu, Zhijie Zhang, Mengdan Zhang, Kekai Sheng, Ke Li, Weiming Dong, Liqing Zhang, Changsheng Xu, Xing Sun. Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2022 Paper, Code
	Removing the Background by Adding the Background: Towards Background Robust Self-supervised Video Representation Learning Jinpeng Wang, Yuting Gao, Ke Li, Yiqi Lin, Andy J Ma, Xing Sun. Computer Vision and Pattern Recognition (CVPR), 2021 Paper, Code
	Architecture Disentanglement for Deep Neural Networks Jie Hu, Liujuan Cao, Qixiang Ye, Tong Tong, ShengChuan Zhang, Ke Li, Feiyue Huang, Rongrong Ji, Ling Shao. International Conference on Computer Vision (ICCV, Oral), 2021 Paper, Code
	Enhancing Unsupervised Video Representation Learning by Decoupling the Scene and the Motion Jinpeng Wang, Yuting Gao, Ke Li, Xinyang Jiang, Xiaowei Guo, Rongrong Ji, Xing Sun. Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2021 Paper, Code
	One for More: Selecting Generalizable Samples for Generalizable ReID Model Enwei Zhang, Xinyang Jiang, Hao Cheng, Ancong Wu, Fufu Yu, Ke Li, Xiaowei Guo, Feng Zheng, Wei-Shi Zheng, Xing Sun. Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2021 Paper
	Pruning Filter in Filter Fanxu Meng, Hao Cheng, Ke Li, Huixiang Luo, Xiaowei Guo, Guangming Lu, Xing Sun. Advances in Neural Information Processing Systems (NeurIPS), 2020 Paper, Code
	Filter Grafting for Deep Neural Networks Fanxu Meng, Hao Cheng, Ke Li, Zhixin Xu, Rongrong Ji, Xing Sun, Gaungming Lu. Computer Vision and Pattern Recognition (CVPR), 2020 Paper, Code
	Asymmetric Co-Teaching for Unsupervised Cross Domain Person Re-Identification Fengxiang Yang, Ke Li, Zhun Zhong, Zhiming Luo, Xing Sun, Hao Cheng, Xiaowei Guo, Feiyue Huang, Rongrong Ji, Shaozi Li. Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2020. Paper, Code
	Semi-Supervised Adversarial Monocular Depth Estimation Rongrong Ji, Ke Li*, Yan Wang, Feng Guo, Xiaowei Guo, Yongjian Wu, Feiyue Huang, and Jiebo Luo. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2019. Paper

More About

• Born in Zhengzhou. Now live in Shanghai.
• Aside from the academic experience, I also hold a B.A. degree in English with TEM-8 passed and had been teaching writing skills in the New Oriental part-time during 2011 to 2014.