胡晓林 - 清华大学 - 计算机科学与技术系

个人简介

I got my PhD degree in Automation and Computer-Aided Engineering from The Chinese University of Hong Kong in 2007, under the supervision of Prof. Jun Wang. Then I became a post-doc researcher at the Department of Computer Science and Technology, Tsinghua University working with Prof. Bo Zhang. Since 2009, I have been a faculty member of this department, working in the TSAIL group directed by Prof. Bo Zhang and Prof. Jun Zhu. My current research interests include artificial neural networks and computational neuroscience. I'm an Associate Editor of IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing and Cognitive Neurodynamics. Previously I was an Associate Editor of IEEE Transactions on Neural Networks and Learning Systems. I'm a Senior Member of IEEE.

研究领域

My main research interest lies in the intersection of deep learning and neuroscience. On one hand, inspired by the brain, I develop new deep learning models to circumvent the difficulties that current deep learning models are facing. On the other hand, using deep learning techniques, I try to unravel the secrete of the brain about how it processes sensory information. One important ongoing project is neuron tracing in mouse brain. My lab also conducts research on various applications of deep learning such as traffic sign detection, face detection, image segmentation, medical image analysis, music generation, etc. In recent years we have conducted many researches on the robustness of neural networks. An interesting application is the creation of "invisible cloaks" for person detectors based on neural networks.

近期论文

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Xiao Li, Jianmin Li, Ting Dai, Jie Shi, Jun Zhu, Xiaolin Hu, “Rethinking Natural Adversarial Examples for Classification Models,” arXiv:2102.1173. Xinyi Li, Yanan Zhong, Hang Chen, Jianshi Tang, Xiaojian Zheng, Wen Sun, Yang Li, Dong Wu, Bin Gao, Xiaolin Hu, He Qian, Huaqiang Wu, “Memristors-based dendritic neuron for high-efficiency spatial-temporal information processing,” Advanced Materials. Early Access. Jianjin Xu, Zhaoxiang Zhang, Xiaolin Hu, “Extracting semantic knowledge from gans with unsupervised learning,” IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023. Early Access. Xiao Li, Ziqi Wang, Bo Zhang, Fuchun Sun, Xiaolin Hu, “Recognizing Object by components with human prior knowledge enhances adversarial robustness of deep neural networks,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 45, no. 7, pp. 8861-8873, July 2023. Hector Martel, Julius Richter, Kai Li, Xiaolin Hu, Timo Gerkmann, “Audio-visual speech separation in noisy environments with a lightweight iterative model,” Proceedings of the INTERSPEECH, Dublin, Ireland, August 20-24, 2023. Chufeng Tang, Lingxi Xie, Xiaopeng Zhang, Xiaolin Hu, Qi Tian, “Visual recognition by request,” Proc. of the 36th IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Vancouver, Canada, June 18-22, 2023. Zhanhao Hu, Wenda Chu, Xiaopei Zhu, Hui Zhang, Bo Zhang, Xiaolin Hu, “Physically realizable natural-looking clothing textures evade person detectors via 3D modeling,” Proc. of the 36th IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Vancouver, Canada, June 18-22, 2023. Kai Li, Runxuan Yang, Xiaolin Hu, “An efficient encoder-decoder architecture with top-down attention for speech separation,” Proc. of the 11th International Conference on Learning Representations (ICLR), Kigali, Rwanda, May 1-5, 2023. Tianren Zhang, Shangqi Guo, Tian Tan, Xiaolin Hu, Feng Chen, “Adjacency constraint for efficient hierarchical reinforcement learning,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 45, no. 4, pp. 4152-4166, 2022. Hang Chen, Chufeng Tang, Xiaolin Hu. "Dense contrastive loss for instance segmentation." Proc. of the British Machine Vision Conference (BMVC), London, UK, Nov. 21-24, 2022. Kai Li, Xiaolin Hu, Yi Luo, “On the use of deep mask estimation module for neural source separation systems,” Proceedings of the InterSpeech, Incheon, Korea, Sept. 18-22, 2022. Haoran Chen, Jianmin Li, Simone Frintrop, and Xiaolin Hu, “The MSR-Video to Text dataset with clean annotations,” Computer Vision and Image Understanding, vol. 225, article no. 103581, 2022. Ting-Yu Kuo, Yuanda Liao, Kai Li, Bo Hong, Xiaolin Hu, “Inferring mechanisms of auditory attentional modulation with deep neural networks,” Neural Computation, vol. 34, no. 11, pp. 2205-2231, 2022. With the help of DNNs, we suggest that the projection of top-down attention signals to lower stages within the auditory pathway of the human brain plays a more significant role than the higher stages in solving the "cocktail party problem". Shangqi Guo, Qi Yan, Xin Su, Xiaolin Hu, Feng Chen, “State-temporal compression in reinforcement learning with the reward-restricted geodesic metric,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 44, no. 9, pp. 5572-5589, 2022. Xiaolin Hu, Chufeng Tang, Hang Chen, Xiao Li, Jianmin Li, Zhaoxiang Zhang, “Improving image segmentation with boundary patch reﬁnement,” International Journal of Computer Vision, vol. 130, pp. 2571-2589, 2022. Chufeng Tang, Lingxi Xie, Gang Zhang, Xiaopeng Zhang, Qi Tian, Xiaolin Hu, “Active pointly-supervised instance segmentation,” Proc. of European Conference on Computer Vision (ECCV), Tel-Aviv, Israel, Oct. 23-27, 2022. We present an economic active learning setting, APIS, for instance segmentation, which saves annotation cost dramatically. Zhanhao Hu, Jun Zhu, Bo Zhang, Xiaolin Hu, “Ampliﬁcation trojan network: attack deep neural networks by amplifying their inherent weakness,” Neurocomputing, vol. 505, pp. 142-153, 2022. Jianfeng Wang, Thomas Lukasiewicz, Daniela Massiceti, Xiaolin Hu, Vladimir Pavlovic, Alexandros Neophytou, “NP-match: when neural processes meet semi-supervised learning,” Proc. of the 39 th International Conference on Machine Learning (ICML), Baltimore, Maryland, USA, July 17-23, 2022. Jianfeng Wang, Xiaolin Hu, “Convolutional neural networks with gated recurrent connections,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 44, no. 7, pp. 3421-3425, 2022. Zhanhao Hu, Siyuan Huang, Xiaopei Zhu, Fuchun Sun, Bo Zhang, Xiaolin Hu, “Adversarial texture for fooling person detectors in the physical world”, Proc. of the 35th IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Orleans, Louisian, June 19-24, 2022. (Oral) Xiaopei Zhu, Zhanhao Hu, Siyuan Huang, Jianmin Li, Xiaolin Hu, “Infrared invisible clothing: hiding from infrared detectors at multiple angles in real world”, Proc. of the 35th IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Orleans, Louisian, June 19-24, 2022. (Oral) Xiaolin Hu, Zhigang Zeng, “Bridging the functional and wiring properties of V1 neurons through sparse coding,” Neural Computation, vol. 34, no. 1, pp. 104-137, 2022. Xiaolin Hu, Kai Li, Weiyi Zhang, Yi Luo, Jean-Marie Lemercier, Timo Gerkmann, “Speech separation using an asynchronous fully recurrent convolutional neural network,” Advances in Neural Information Processing Systems (NeurIPS), Virtual, Dec 6-14, 2021. Hang Chen, Xiao Li, Zefan Wang, Xiaolin Hu, “Robust logo detection in E-commerce images by data augmentation,” Proc. of the 29th ACM International Conference on Multimedia Workshop, pp. 4789-4793, Chengdu, China, Oct 20-24, 2021. Jiaheng Liu, Yudong Wu, Yichao Wu, Chuming Li, Xiaolin Hu, Ding Liang, Mengyu Wang, “DAM: Discrepancy Alignment Metric for Face Recognition; Proc. of the IEEE/CVF International Conference on Computer Vision (ICCV), pp. 3814-3823, Virtual, Oct 11-17, 2021. Ge Gao, Mikko Lauri, Xiaolin Hu, Jianwei Zhang, Simone Frintrop, “CloudAAE: learning 6D object pose regression with on-line data synthesis on point clouds,” Proc. of the IEEE International Conference on Robotics and Automation (ICRA), Xi’an, China, May 30-June 5, 2021. Gang Zhang, Xin Lu, Jingru Tan, Jianmin Li, Zhaoxiang Zhang, Quanquan Li, Xiaolin Hu, “RefineMask: Towards high-quality instance segmentation with fine-grained features,“ Proc. of the 34th IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Virtual, June 19-25, 2021. Chufeng Tang, Hang Chen, Xiao Li, Jianmin Li, Zhaoxiang Zhang, Xiaolin Hu, “Look closer to segment better: boundary patch refinement for instance segmentation,” Proc. of the 34th IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Virtual, June 19-25, 2021. Jianfeng Wang, Thomas Lukasiewicz, Xiaolin Hu, Jianfei Cai, Zhenghua Xu, “RSG: A simple yet effective module for learning imbalanced datasets,” Proc. of the 34th IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Virtual, June 19-25, 2021. Xiang Li, Wenhai Wang, Xiaolin Hu, Jun Li, Jinhui Tang, Jian Yang, “Generalized Focal Loss V2: learning reliable localization quality estimation for dense object detection,” Proc. of the 34th IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Virtual, June 19-25, 2021. Weiyi Zhang, Shuning Zhao, Le Liu, Jianmin Li, Xingliang Cheng, Thomas Fang Zheng, Xiaolin Hu,“Attack on practical speaker verification system using universal adversarial perturbations,” IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Virtual, June 6-11, 2021. Xiaopei Zhu, Xiao Li, Jianmin Li, Zheyao Wang, Xiaolin Hu, “Fooling thermal infrared pedestrian detectors in real world using small bulbs,” The Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI), Virtual, Feb 2-9, 2021. Han Liu, Shifeng Zhang, Ke Lin, Jing Wen, Jianmin Li, Xiaolin Hu, “Vocabulary-wide credit assignment for training image captioning models,” IEEE Transactions on Image Processing, vol. 30, pp. 2450-2460, 2021. Zi Yin, Valentin Yiu, Xiaolin Hu, Liang Tang, “End-to-end face parsing via interlinked convolutional neural networks,” Cognitive Neurodynamics, vol. 15, pp. 169-179, 2021. Tianren Zhang, Shangqi Guo, Tian Tan, Xiaolin Hu, Feng Chen, “Generating adjacency-constrained subgoals in hierarchical reinforcement learning,” Advances in Neural Information Processing Systems (NeurIPS), Dec 6-12, 2020. Xiang Li, Wenhai Wang, Lijun Wu, Shuo Chen, Xiaolin Hu, Jun Li, Jinhui Tang, Jian Yang, “Generalized focal loss: learning qualified and distributed bounding boxes for dense object detection,” Advances in Neural Information Processing Systems (NeurIPS), Dec 6-12, 2020. Haoran Chen, Ke Lin, Alexander Maye, Jianming Li, and Xiaolin Hu, “A semantics-assisted video captioning model trained with scheduled sampling,” Frontiers in Robotics and AI, September 30, 2020. Weilun Chen, Zhaoxiang Zhang, Xiaolin Hu, Baoyuan Wu, “Boosting decision-based black-box adversarial attacks with random sign flip,” European Conference on Computer Vision, pp. 276-293. Springer, Cham, 2020. Jian Wu, Xiaoguang Liu, Xiaolin Hu, Jun Zhu, “PopMNet: generating structured pop music melodies using neural networks,” Artificial Intelligence, vol. 286, article 103303, 2020. Yulong Wang, Hang Su, Bo Zhang, Xiaolin Hu, “Learning reliable visual saliency for model explanations, ” IEEE Transactions on Multimedia, vol. 22, no. 7, pp. 1796-1807, 2020. Yulong Wang, Hang Su, Bo Zhang, Xiaolin Hu, “Interpret neural networks by extracting critical subnetworks,” IEEE Transactions on Image Processing, vol. 29, pp. 6707-6720, 2020. Jian Wu, Changran Hu, Yulong Wang, Xiaolin Hu, Jun Zhu, “A hierarchical recurrent neural network for symbolic melody generation,” IEEE Transactions on Cybernetics, vol. 50, no. 6, pp. 2749-2757, 2020. Jianqiao Guo, Yajun Yin, Xiaolin Hu, Gexue Ren, “Self-similar network model for fractional-order neuronal spiking: implications of dendritic spine functions,” Nonlinear Dynamics, vol. 100, pp. 921-935, 2020. Haoran Chen and Jianmin Li and Xiaolin Hu, “Delving deeper into the decoder for video captioning,” The 24th European Conference on Artificial Intelligence (ECAI), Santiago de Compostela, Spain, August 29-September 2, 2020. Ge Gao, Mikko Lauri, Yulong Wang, Xiaolin Hu, Jianwei Zhang, Simone Frintrop, “6D object pose regression via supervised learning on point clouds,” IEEE International Conference on Robotics and Automation (ICRA), Paris, France, May 31 to June 4, 2020. Qiushan Guo, Xinjiang Wang, Yichao Wu, Zhipeng Yu, Ding Liang, Xiaolin Hu and Ping Luo, “Online knowledge distillation via collaborative learning,” Proc. of the 33th IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, USA, June 16-18, 2020. Yudong Wu, Yichao Wu, Ruihao Gong, Yuanhao Lv, Ken Chen, Ding Liang, Xiaolin Hu, Xianglong Liu and Junjie Yan, “Rotation consistent margin loss for efficient low-bit face recognition”, Proc. of the 33th IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, USA, June 16-18, 2020. Yulong Wang, Xiaolu Zhang, Xiaolin Hu, Bo Zhang, Hang Su, “Dynamic network pruning with interpretable layerwise channel selection, ”The Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI), New York, USA, Feb 7-12, 2020. Yulong Wang, Xiaolu Zhang, Lingxi Xie, Jun Zhou, Hang Su, Bo Zhang, Xiaolin Hu, “Pruning from scratch,” The Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI), New York, USA, Feb 7-12, 2020 Xiang Li, Jun Li, Xiaolin Hu, Jian Yang, “Line-CNN: end-to-end traffic line detection with line proposal unit,” IEEE Transactions on Intelligent Transportation Systems, vol. 21, no. 1, pp. 248-258, 2020. Fangzhou Liao, Ming Liang, Zhe Li, Xiaolin Hu, Sen Song, “Evaluate the malignancy of pulmonary nodules using the 3-D deep leaky noisy-or network, ” IEEE Transactions on Neural Networks and Learning Systems, vol. 30, no. 11, pp. 3484-3495, 2019. Chufeng Tang, Lu Sheng, Zhaoxiang Zhang, Xiaolin Hu, “Improving pedestrian attribute recognition with weakly-supervised multi-scale attribute-specific localization,” Proc. of IEEE International Conference on Computer Vision (ICCV), Seoul, Korea, Oct 27–Nov 2, 2019. pp. 4997-5006. Xiao Jin, Baoyun Peng, Yichao Wu, Yu Liu, Jiaheng Liu, Ding Liang, Junjie Yan, Xiaolin Hu, “Knowledge distillation via route constrained optimization,” Proc. of IEEE International Conference on Computer Vision (ICCV), Seoul, Korea, Oct 27–Nov 2, 2019. pp. 1345-1354. Xiang Li, Shuo Chen, Xiaolin Hu, Jian Yang, “Understanding the Disharmony Between Dropout and Batch Normalization by Variance Shift,” Proc. of the 32th IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Long Beach, USA, June 15–21, 2019. Xiang Li, Wenhai Wang, Xiaolin Hu, Jian Yang, “Selective Kernel Networks,” Proc. of the 32th IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Long Beach, USA, June 15–21, 2019. Niange Yu, Xiaolin Hu, Binheng Song, Jian Yang, Jianwei Zhang, “Topic-oriented image captioning based on order-embedding,” IEEE Transactions on Image Processing, vol. 28, no. 6, pp. 2743-2754, 2019. Shangqi Guo , Zhaofei Yu, Fei Deng, Xiaolin Hu, Feng Chen, “Hierarchical Bayesian inference and learning in spiking neural networks,” IEEE Transactions on Cybernetics, vol. 49, no. 1, pp. 133-145, 2019. Fangzhou Liao, Xi Chen, Xiaolin Hu, Sen Song, “Estimation of the volume of the left ventricle from MRI images using deep neural networks,” IEEE Transactions on Cybernetics, vol. 49, no. 2, pp. 495-504, 2019. Qingtian Zhang, Xiaolin Hu, Bo Hong, Bo Zhang, “A hierarchical sparse coding model predicts acoustic feature encoding in both auditory midbrain and cortex,” PLOS Computational Biology, 15(2): e1006766, 2019. Wei Feng, Wentao Liu, Tong Li, Jing Peng, Chen Qian, Xiaolin Hu, “Turbo learning framework for human-object interactions recognition and human pose estimation,” The Thirty-Third AAAI Conference on Artificial Intelligence (AAAI), Honolulu, Hawaii, USA, Jan 27-Feb 1, 2019. Yi Zhang, Weichao Qiu, Qi Chen, Xiaolin Hu, Alan Yuille, “UnrealStereo: controlling hazardous factors to analyze stereo vision”, Proc. of the International Conference on 3DVision, Verona, Italy, September 5-8, 2018. Fangzhou Liao, Ming Liang, Yinpeng Dong, Tianyu Pang, Xiaolin Hu, Jun Zhu, “Defense against adversarial attacks using high-level representation guided denoiser,” Proc. of the 31th IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Salt Lake City, USA, June 18-22, 2018. Winning solution of the NIPS 2017 Competition on Adversarial Attacks and Defenses organized by Google Brain. Yinpeng Dong, Fangzhou Liao, Tianyu Pang, Hang Su, Jun Zhu, Xiaolin Hu, Jianguo Li, “Boosting adversarial attacks with momentum,” Proc. of the 31th IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Salt Lake City, USA, June 18-22, 2018. Yulong Wang, Hang Su, Bo Zhang, Xiaolin Hu, “Interpret neural networks by identifying critical data routing paths,” Proc. of the 31th IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Salt Lake City, USA, June 18-22, 2018. Bo Li, Junjie Yan, Wei Wu, Zheng Zhu, Xiaolin Hu, “High Performance Visual Tracking with Siamese Region Proposal Network,” Proc. of the 31th IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Salt Lake City, USA, June 18-22, 2018. Wentao Liu, Jie Chen, Cheng Li, Chen Qian, Xiao Chu, Xiaolin Hu, “A cascaded inception of inception network with attention modulated feature fusion for human pose estimation,” The Thirty-Second AAAI Conference on Artificial Intelligence (AAAI), New Orleans, USA, Feb 2-7, 2018. Chengxu Zhuang, Yulong Wang, Daniel Yamins, Xiaolin Hu, “Deep learning predicts correlation between a functional signature of higher visual areas and sparse firing of neurons,” Frontiers in Computational Neuroscience, 2017. Doi: 10.3389/fncom.2017.00100 Jianfeng Wang, Xiaolin Hu, “Gated recurrent convolution neural network for OCR,” Advancies in Neural Information Processing (NIPS), Long Beach, USA, Dec. 4-9, 2017. Zekun Hao, Yu Liu, Hongwei Qin, Junjie Yan, Xiu Li, Xiaolin Hu, “Scale-aware face detection,” Proc. of the 30th IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu, USA, July 21–26, 2017. Tiancheng Sun, Yulong Wang, Jian Yang, Xiaolin Hu, “Convolution neural networks with two pathways for image style recognition,” IEEE Transactions on Image Processing, vol. 26, no. 9, pp. 4102-4113, 2017. J. Wu, L. Ma, X. Hu, “Delving deeper into convolutional neural networks for camera relocalization,” Proc. of IEEE International Conference on Robotics and Automation (ICRA), Singapore, May 29- June 3, 2017. Y. Zhao, X. Jin, X. Hu, “Recurrent convolutional neural network for speech processing,” Proc. of the 42nd IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), New Orleans, USA, March 5-9, 2017. Q. Zhang, X. Hu, H. Luo, J. Li, X. Zhang, B. Zhang, “Deciphering phonemes from syllables in blood oxygenation level-dependent signals in human superior temporal gyrus,” European Journal of Neuroscience, vol. 43, no. 6, pp. 773-781, 2016.