Wenbin Li at Nanjing University

Wenbin Li (李文斌)
Associate Professor

Reasoning and Learning Research Group
School of Intelligence Science and Technology
State Key Laboratory for Novel Software Technology
Nanjing University, Suzhou Campus

Email: liwenbin@nju.edu.cn; liwenbin.nju@gmail.com

Google Scholar | Github | Github-VIG

• Dongdong Ren, Wenbin Li, Tianyu Ding, Lei Wang, Qi Fan, Jing Huo, Hongbing Pan and Yang Gao.
  ONNXPruner: ONNX-Based General Model Pruning Adapter.
  In: arXiv preprint arXiv:2404.08016, 2024.
  

• Wenbin Li, Meihao Kong, Xuesong Yang, Lei Wang, Jing Huo, Yang Gao and Jiebo Luo.
  A Unified Framework for Contrastive Learning from a Perspective of Affinity Matrix.
  In: arXiv preprint arXiv:2211.14516, 2022.
  

• Changbin Shao, Wenbin Li*, Jing Huo, Zhenhua Feng, Yang Gao.
  Attention-based Investigation and Solution to the Trade-off Issue of Adversarial Training.
  In: Neural Networks, 2024.
  (Impact Factor: 7.8)
  [Paper] [Code]

• Jing Huo, Meihao Kong, Wenbin Li, Jing Wu, Yu-Kun Lai, Yang Gao.
  Towards Efficient Image and Video Style Transfer via Distillation and Learnable Feature Transformation.
  In: Computer Vision and Image Understanding (CVIU), 2024.
  (Impact Factor: 4.5)
  [Paper] [Demo]

• Wenbin Li, Ziyi Wang, Xuesong Yang, Chuanqi Dong, Pinzhuo Tian, Tiexin Qin, Jing Huo, Yinghuan Shi, Lei Wang, Yang Gao and Jiebo Luo.
  LibFewShot: A Comprehensive Library for Few-shot Learning.
  In: IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023.
  (Impact Factor: 23.6)
  [Paper] [Code]

• Wenbin Li, Lei Wang, Xingxing Zhang, Lei Qi, Jing Huo, Yang Gao, Jiebo Luo.
  Defensive Few-shot Learning.
  In: IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023.
  (Impact Factor: 23.6)
  [Paper] [Code]

• Wenbin Li, Xuesong Yang, Meihao Kong, Lei Wang, Jing Huo, Yang Gao and Jiebo Luo.
  Trip-ROMA: Self-Supervised Learning with Triplets and Random Mappings.
  In: Transactions on Machine Learning Research (TMLR), 2023.
  [Paper] [Code]

• Shaokang Dong, Hangyu Mao, Shangdong Yang, Shengyu Zhu, Wenbin Li*, Jianye Hao, Yang Gao
  WToE: Learning When to Explore in Multiagent Reinforcement Learning.
  In: IEEE Transactions on Cybernetics (TCYB), 2023.
  (Impact Factor: 11.8)
  

• Boyao Shi, Wenbin Li*, Jing Huo, Pengfei Zhu, Lei Wang, Yang Gao.
  Global- and Local-aware Feature Augmentation with Semantic Orthogonality for Few-shot Image Classification.
  In: Pattern Recognition, 2023.
  (Impact Factor: 8.0)
  [Paper] [Code]

• Jing Huo, Xiangde Liu, Wenbin Li, Yang Gao, Hujun Yin, Jiebo Luo.
  CAST: Learning Both Geometric and Texture Style Transfers for Effective Caricature Generation.
  In: IEEE Transactions on Image Processing (TIP), 2022.
  (Impact Factor: 10.6)
  [Paper]

• Wenbin Li, Yanfang Liu, Jing Huo, Yinghuan Shi, Yang Gao, Lei Wang, Jiebo Luo.
  A Multilayer Framework for Online Metric Learning.
  In: IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022.
  (Impact Factor: 10.4)
  

• Yanfang Liu, Xiaocong Fan, Wenbin Li, Yang Gao.
  Online Passive-Aggressive Active Learning for Trapezoidal Data Streams.
  In: IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022.
  (Impact Factor: 10.4)
  [Paper]

• Pinzhuo Tian, Wenbin Li, Yang Gao.
  Consistent Meta-Regularization for Better Meta-Knowledge in Few-Shot Learning.
  In: IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2021.
  (Impact Factor: 10.4)
  [Paper]

• Zheng Gu, Chuanqi Dong, Jing Huo, Wenbin Li, Yang Gao.
  CariMe: Unpaired Caricature Generation with Multiple Exaggerations.
  In: IEEE Transactions on Multimedia (TMM), 2021.
  (Impact Factor: 7.3)
  [Paper] [Code]

• Wenbin Li, Wei Xiong, Haofu Liao, Jing Huo, Yang Gao, Jiebo Luo.
  CariGAN: Caricature Generation through Weakly Paired Adversarial Learning.
  In: Neural Networks, 2020.
  (Impact Factor: 7.8)
  [Paper]

• Zhenxing Ge, Zheng Xu, Tianyu Ding, Linjian Meng, Bo An, Wenbin Li, Yang Gao.
  Safe and Robust Subgame Exploitation in Imperfect Information Games.
  In: International Conference on Machine Learning (ICML), 2024.
  (Acceptance Rate: 2609/9473=27.5%)
  

• Chao Li, Yujing Hu, Shangdong Yang, Tangjie Lv, Changjie Fan, Wenbin Li*, Chongjie Zhang, Yang Gao*.
  STAR: Spatio-Temporal State Compression for Multi-Agent Tasks with Rich Observations.
  In: International Joint Conference on Artificial Intelligence (IJCAI), 2024.
  

• Rui Yan, Hongyu Qu, Xiangbo Shu, Wenbin Li*, Jinghui Tang, Tieniu Tan.
  DTS-TPT: Dual Temporal-Sync Test-time Prompt Tuning for Zero-shot Activity Recognition.
  In: International Joint Conference on Artificial Intelligence (IJCAI), 2024.
  

• Wenxiao Deng, Wenbin Li*, Tianyu Ding, Lei Wang, Hongguang Zhang,
  Kuihua Huang, Jing Huo, and Yang Gao.
  Exploiting Inter-sample and Inter-feature Relations in Dataset Distillation.
  In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2024.
  (Acceptance Rate: 2719/11532=23.6%)
  [arXiv] [Code]

• Yanqi Bao, Tianyu Ding, Jing Huo, Wenbin Li, Yuxin Li, and Yang Gao.
  InsertNeRF: Instilling Generalizability into NeRF with HyperNet Modules.
  In: International Conference on Learning Representations (ICLR), 2024.
  (Acceptance Rate: 2251/7262=31%)
  [Paper] [Code]

• Chao Li , Yupeng Zhang, Jianqi Wang, Yujing Hu, Shaokang Dong, Wenbin Li,
  Tangjie Lv, Changjie Fan, Yang Gao.
  Optimistic Value Instructors for Cooperative Multi-Agent Reinforcement Learning.
  In: AAAI Conference on Artificial Intelligence (AAAI), 2024.
  (Acceptance Rate: 2342/9862=23.75%)
  

• Zhenxing Ge, Zheng Xu, Tianyu Ding, Wenbin Li*, Yang Gao*.
  Efficient Subgame Refinement for Extensive-form Games.
  In: Conference on Neural Information Processing Systems (NeurIPS), 2023.
  (Acceptance Rate: 3222/12343=26.1%)
  

• Yanqi Bao, Yuxin Li, Jing Huo, Tianyu Ding, Xinyue Liang, Wenbin Li, Yang Gao.
  Where and How: Mitigating Confusion in Neural Radiance Fields from Sparse Inputs.
  In: ACM Conference on Multimedia (ACM MM), 2023.
  (Acceptance Rate: 902/3072=29.3%)
  

• Min Zhang, Junkun Yuan, Yue He, Wenbin Li, Zhengyu Chen, Kun Kuang.
  MAP: Towards Balanced Generalization of IID and OOD through Model-Agnostic Adapters.
  In: International Conference on Computer Vision (ICCV), 2023. [Oral]
  

• Wenbin Li, Zhichen Fan, Jing Huo, Yang Gao.
  Modeling Inter-Class and Intra-Class Constraints in Novel Class Discovery.
  In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
  (Acceptance Rate: 2360/9155=25.78%)
  [Paper] [Code]

• Wubing Chen, Wenbin Li*, Xiao Liu, Shangdong Yang, Yang Gao*.
  Learning Explicit Credit Assignment for Cooperative Multi-Agent Reinforcement Learning
  via Polarization Policy Gradient.
  In: AAAI Conference on Artificial Intelligence (AAAI), 2023.
  (Acceptance Rate: 1721/8777=19.6%)
  [Paper] [Code]

• Min Zhang, Siteng Huang, Wenbin Li, Donglin Wang.
  Tree Structure-Aware Few-Shot Image Classification via Hierarchical Aggregation.
  In: European Conference on Computer Vision (ECCV), 2022.
  (Acceptance Rate: 1650/5803=28%)
  [Paper] [Code]

• Zheng Gu^#, Wenbin Li^#, Jing Huo, Lei Wang, Yang Gao.
  LoFGAN: Fusing Local Representations for Few-shot Image Generation.
  In: International Conference on Computer Vision (ICCV), 2021.
  (Acceptance Rate: 1617/6236=25.9%) [# Equal contribution]
  [Paper] [Code]

• Jing Huo, Shiyin Jin, Wenbin Li, Jing Wu, Yu-Kun Lai, Yinghuan Shi, Yang Gao.
  Manifold Alignment for Semantically Aligned Style Transfer.
  In: International Conference on Computer Vision (ICCV), 2021. [Oral]
  (Acceptance Rate: 1617/6236=25.9%; Oral: 210/6236=3%)
  [Paper] [Code]

• Wenbin Li, Lei Wang, Jing Huo, Yinghuan Shi, Yang Gao, Jiebo Luo.
  Asymmetric Distribution Measure for Few-shot Learning.
  In: International Joint Conference on Artificial Intelligence (IJCAI), 2020.
  (Acceptance Rate: 592/4717=12.6%)
  [Paper] [Code]

• Chuanqi Dong, Wenbin Li, Jing Huo, Zheng Gu, Yang Gao.
  Learning Task-aware Local Representations for Few-shot Learning.
  In: International Joint Conference on Artificial Intelligence (IJCAI), 2020.
  (Acceptance Rate: 592/4717=12.6%)
  [Paper] [Code]

• Jinglin Xu, Xiangsen Zhang, Wenbin Li, Xinwang Liu, Junwei Han.
  Joint Multi-view 2D Convolutional Neural Networks for 3D Object Classification.
  In: International Joint Conference on Artificial Intelligence (IJCAI), 2020.
  (Acceptance Rate: 592/4717=12.6%)
  [Paper]

• Changbin Shao, Jing Huo, Lei Qi, Zhen-Hua Feng, Wenbin Li, Chuanqi Dong, Yang Gao.
  Biased Feature Learning for Occlusion Invariant Face Recognition.
  In: International Joint Conference on Artificial Intelligence (IJCAI), 2020.
  (Acceptance Rate: 592/4717=12.6%)
  [Paper]

• Jinglin Xu, Wenbin Li, Xinwang Liu, Dingwen Zhang, Ji Liu, Junwei Han.
  Deep Embedded Complementary and Interactive Information for Multi-view Classification.
  In: AAAI Conference on Artificial Intelligence (AAAI), 2020.
  (Acceptance Rate: 1591/7737=20.6%)
  [Paper] [Code]

• Xiao Liu, Wenbin Li, Jing Huo, Lili Yao, Yang Gao.
  Layerwise Sparse Coding for Pruned Deep Neural Networks with Extreme Compression Ratio.
  In: AAAI Conference on Artificial Intelligence (AAAI), 2020.
  (Acceptance Rate: 1591/7737=20.6%)
  [Paper]

• Wenbin Li, Lei Wang, Jinglin Xu, Jing Huo, Yang Gao, Jiebo Luo.
  Revisiting Local Descriptor based Image-to-Class Measure for Few-shot Learning.
  In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019.
  (Acceptance Rate: 1299/5165=25.2%)
  [Paper] [Code]

• Wenbin Li^#, Jinglin Xu^#, Jing Huo, Lei Wang, Yang Gao, Jiebo Luo.
  Distribution Consistency based Covariance Metric Networks for Few-shot Learning.
  In: AAAI Conference on Artificial Intelligence (AAAI), 2019. [Oral]
  (Acceptance Rate: 1150/7095=16.2%) [# Equal contribution]
  [Paper] [Slides] [Code]