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Jingfeng Zhang
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Towards Adversarially Robust Deep Image Denoising


Jan 13, 2022
Hanshu Yan, Jingfeng Zhang, Jiashi Feng, Masashi Sugiyama, Vincent Y. F. Tan

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DRDF: Determining the Importance of Different Multimodal Information with Dual-Router Dynamic Framework


Jul 21, 2021
Haiwen Hong, Xuan Jin, Yin Zhang, Yunqing Hu, Jingfeng Zhang, Yuan He, Hui Xue

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RAMS-Trans: Recurrent Attention Multi-scale Transformer forFine-grained Image Recognition


Jul 17, 2021
Yunqing Hu, Xuan Jin, Yin Zhang, Haiwen Hong, Jingfeng Zhang, Yuan He, Hui Xue

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Reliable Adversarial Distillation with Unreliable Teachers


Jun 09, 2021
Jianing Zhu, Jiangchao Yao, Bo Han, Jingfeng Zhang, Tongliang Liu, Gang Niu, Jingren Zhou, Jianliang Xu, Hongxia Yang

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NoiLIn: Do Noisy Labels Always Hurt Adversarial Training?


May 31, 2021
Jingfeng Zhang, Xilie Xu, Bo Han, Tongliang Liu, Gang Niu, Lizhen Cui, Masashi Sugiyama

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Guided Interpolation for Adversarial Training


Feb 15, 2021
Chen Chen, Jingfeng Zhang, Xilie Xu, Tianlei Hu, Gang Niu, Gang Chen, Masashi Sugiyama

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CIFS: Improving Adversarial Robustness of CNNs via Channel-wise Importance-based Feature Selection


Feb 10, 2021
Hanshu Yan, Jingfeng Zhang, Gang Niu, Jiashi Feng, Vincent Y. F. Tan, Masashi Sugiyama

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Understanding the Interaction of Adversarial Training with Noisy Labels


Feb 09, 2021
Jianing Zhu, Jingfeng Zhang, Bo Han, Tongliang Liu, Gang Niu, Hongxia Yang, Mohan Kankanhalli, Masashi Sugiyama

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Learning Diverse-Structured Networks for Adversarial Robustness


Feb 08, 2021
Xuefeng Du, Jingfeng Zhang, Bo Han, Tongliang Liu, Yu Rong, Gang Niu, Junzhou Huang, Masashi Sugiyama

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* 26 pages, 8 figures 
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