Ke Li (李珂)

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Senior Researcher and Team Manager @Tencent

Bio

I am a senior researcher and team manager at Tencent Youtu Lab. My research interests lie in the area of deep learning and its application in computer vision and natural language processing. 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

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)

drawing Weakly Supervised Open-Vocabulary Object Detection
Jianghang Lin, Yunhang Shen, Bingquan Wang, Shaohui Lin, Ke Li, Liujuan Cao.
Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2024
Paper
drawing SPD-DDPM: Denoising Diffusion Probabilistic Models in the Symmetric Positive Definite Space
Yunchen Li, Zhou Yu, Gaoqi He, Yunhang Shen, Ke Li, Xing Sun, Shaohui Lin.
Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2024
Paper
drawing Semi-Supervised Blind Image Quality Assessment through Knowledge Distillation and Incremental Learning
Wensheng Pan, Timin Gao, Yan Zhang, Xiawu Zheng, Yunhang Shen, Ke Li, Runze Hu, Yutao Liu, Pingyang Dai.
Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2024
Paper
drawing SoftCLIP: Softer Cross-modal Alignment Makes CLIP Stronger
Yuting Gao, Jinfeng Liu, Zihan Xu, Tong Wu, Enwei Zhang, Ke Li, Jie Yang, Wei Liu, Xing Sun.
Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2024
Paper
drawing CAPro: Webly Supervised Learning with Cross-modality Aligned Prototypes
Yulei Qin, Xingyu Chen, Yunhang Shen, Chaoyou Fu, Yun Gu, Ke Li, Xing Sun, Rongrong Ji.
Advances in Neural Information Processing Systems (NeurIPS), 2023.
Paper, CodeGitHub stars
drawing Multi-modal Queried Object Detection in the Wild
Yifan Xu, Mengdan Zhang, Chaoyou Fu, Peixian Chen, Xiaoshan Yang, Ke Li, Changsheng Xu.
Advances in Neural Information Processing Systems (NeurIPS), 2023.
Paper, CodeGitHub stars
drawing 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
drawing 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, CodeGitHub stars
drawing Woodpecker: Hallucination Correction for Multimodal Large Language Models
Shukang Yin, Chaoyou Fu, Sirui Zhao, Tong Xu, Hao Wang, Dianbo Sui, Yunhang Shen, Ke Li, Xing Sun, Enhong Chen.
arxiv, 2023
Paper, CodeGitHub stars
drawing MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models
Chaoyou Fu, Peixian Chen, Yunhang Shen, Yulei Qin, Mengdan Zhang, Xu Lin, Jinrui Yang, Xiawu Zheng, Ke Li*, Xing Sun, Rongrong Ji.
arxiv, 2023
Paper, CodeGitHub stars
drawing A Survey on Multimodal Large Language Models
Shukang Yin , Chaoyou Fu, Sirui Zhao, Ke Li, Xing Sun, Tong Xu, Enhong Chen.
arxiv, 2023
Paper, CodeGitHub stars
drawing 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, CodeGitHub stars
drawing 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
drawing 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, CodeGitHub stars
drawing 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, CodeGitHub stars
drawing 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, CodeGitHub stars
drawing 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, CodeGitHub stars
drawing 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, CodeGitHub stars
drawing 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, CodeGitHub stars
drawing 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, CodeGitHub stars
drawing 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, CodeGitHub stars
drawing 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
drawing 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, CodeGitHub stars
drawing 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, CodeGitHub stars
drawing 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, CodeGitHub stars
drawing 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, CodeGitHub stars
drawing 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, CodeGitHub stars
drawing 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
drawing 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, CodeGitHub stars
drawing 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, CodeGitHub stars
drawing 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, CodeGitHub stars
drawing 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

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