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Shuhang Gu

[email protected]

Sternwartstrasse 7, ETH Zentrum
8092
Zurich
Switzerland

github.com/ShuhangGu

About Me

I am a professor with the School of Computer Science and Engineering, University of Electronic Science and Technology of China(UESTC). I obtained my PhD degree under the supervision of Prof. Lei Zhang from The Hong Kong Polytechnic University in 2017. After graduation, I worked as a postdoctoral researcher at the Computer Vision Laboratory (CVL), ETH Zurich, under the supervision of Prof. Luc Van Gool. At CVL, I worked closely with Dr. Radu Timofte.


I am looking for self-motivated graduate students in UESTC. Please send me your CV if you are interested.

Preprints

  1. Weiyi You, Mingyang Zhang, Leheng Zhang, Kexuan Shi, Xingyu Zhou, Shuhang Gu. Consistency Trajectory Matching for One-Step Generative Super-Resolution. [Arxiv]
  2. Kexuan Shi, Hai Chen, Leheng Zhang, Shuhang Gu. Inductive Gradient Adjustment For Spectral Bias In Implicit Neural Representations. [Arxiv]
  3. Jinhua Zhang, Hualian Sheng, Sijia Cai, Bing Deng, Qiao Liang, Wen Li, Ying Fu, Jieping Ye, Shuhang Gu. PerlDiff: Controllable Street View Synthesis Using Perspective-Layout Diffusion Models. [Arxiv]

 

Journal Papers

  1. Xin Deng, Enpeng Liu, Chao Gao, Shengxi Li, Shuhang Gu and Mai Xu. CrossHomo: Cross-Modality and Cross-Resolution Homography Estimation. IEEE TPAMI, 2024.
  2. Zhihua Wang, Keshuo Xu, Yang Yang, Jianlei Dong, Shuhang Gu, Lihao Xu, Yuming Fang and Kede Ma. Measuring Perceptual Color Differences of Smartphone Photographs. IEEE TPAMI, 2023.
  3. Mu Li, Jinxing Li, Shuhang Gu, Feng Wu, David Zhang. End-to-end optimized 360 image compression. IEEE TIP, 2022.
  4. Kaisiyuan Wang, Lu Sheng, Shuhang Gu, Dong Xu. VPU: a video-based point cloud upsampling framework. IEEE TIP, 2022.
  5. Zhenghao Chen, Shuhang Gu, Guo Lu and Dong Xu. Exploiting intra-slice and inter-slice redundancy for learning-based lossless volumetric image compression. IEEE TIP, 2022.
  6. Boyun Li, Yuanbiao Gou, Shuhang Gu, Jerry Zitao Liu, Joey Tianyi Zhou and Xi Peng. You only look yourself: Unsupervised and untrained single image dehazing neural network. IJCV, 2021.
  7. Jinxing Li, Dandan Fan, Lingxiao Yang, Shuhang Gu, Guangming Lu, Yong Xu and David Zhang. Layer-output guided complementary attention learning for image defocus blur detection. IEEE TIP, 2021.
  8. Xin Deng, Yutong Zhang, Mai Xu, Shuhang Gu and Yiping Duan. Deep coupled feedback network for joint exposure fusion and image super-resolution. IEEE TIP, 2021.
  9. Mu Li, Wangmeng Zuo, Shuhang Gu, Jane You and David Zhang. Learning Content-Weighted Deep Image Compression. IEEE T-PAMI, 2020.
  10. Shuhang Gu, Shi Guo, Wangmeng Zuo, Yunjin Chen, Radu Timofte, Luc Van Gool and Lei Zhang. Learned Dynamic Guidance for Depth Image Reconstruction. IEEE TPAMI, 2019. [PDF and code are coming soon.]
  11. Jianrui Cai, Shuhang Gu and Lei Zhang. Learning a Deep Single Image Contrast Enhancer from Multi-Exposure Images. IEEE TIP, 2018. [PDF] [Code]
  12. Jianbo Jiao, Qingxiong Yang, Shengfeng He, Shuhang Gu and Lei Zhang. Joint Image Denoising and Disparity Estimation via Stereo Structure PCA and Noise-tolerant Cost. IJCV, 2018.
  13. Shuhang Gu, Qi Xie, Deyu Meng, Wangmeng Zuo, Xiangchu Feng and Lei Zhang. Weighted Nuclear Norm Minimization and Its Applications to Low Level Vision. IJCV, 2017. [PDF] [Code Denoise] [Code RPCA] [Code MC]
  14. Yuan Xie, Shuhang Gu, Yan Liu, Wangmeng Zuo, Wensheng Zhang and Lei Zhang. Weighted Schatten p-Norm Minimization for Image Denoising and Background Subtraction. IEEE TIP, 2017. [PDF] [Code]
  15. Wamgmeng Zuo, Dongwei Ren, David Zhang, Shuhang Gu and Lei Zhang. Learning Iteration-wise Generalized Shrinkage-Thresholding Operators for Blind Deconvolution. IEEE TIP, 2016.

 

Conference Papers

  1. Leheng Zhang, Weiyi You, Kexuan Shi, Shuhang Gu. Uncertainty-guided Perturbation for Image Super-Resolution Diffusion Model. IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2025. [PDF][Code]
  2. Wei Long, Xingyu Zhou, Leheng Zhang, Shuhang Gu. Progressive Focused Transformer for Single Image Super-Resolution. IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2025. [PDF][Code]
  3. Jingbo Lu, Leheng Zhang, Xingyu Zhou, Mu Li, Wen Li, Shuhang Gu. Learned Image Compression with Dictionary-based Entropy Model. IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2025. [PDF][Code]
  4. Minghao Han, Shiyin Jiang, Shengxi Li, Xin Deng, Mai Xu, Ce Zhu, Shuhang Gu. Causal Context Adjustment Loss for Learned Image Compression. Neural Information Processing Systems (NeurIPS), 2024. [PDF][Code]
  5. Leheng Zhang, Yawei Li, Xingyu Zhou, Xiaorui Zhao and Shuhang Gu. Transcending the Limit of Local Window: Advanced Super-Resolution Transformer with Adaptive Token Dictionary. IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2024. [PDF][Code]
  6. Kexuan Shi, Xingyu Zhou and Shuhang Gu. Improved Implicit Neural Representation with Fourier Bases Reparameterized Training. IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2024. [PDF][Code]
  7. Xingyu Zhou, Leheng Zhang, Xiaorui Zhao, Keze Wang, Leida Li and Shuhang Gu. Video Super-Resolution Transformer with Masked Inter&Intra-Frame Attention. IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2024. [PDF][Code]
  8. Jiale Tao, Shuhang Gu, Wen Li, Lixin Duan. Learning Motion Refinement for Unsupervised Face Animation. Neural Information Processing Systems (NeurIPS), 2023. [PDF]
  9. Ce Liu, Suryansh Kumar, Shuhang Gu, Radu Timofte and Luc Van Gool. VA-DepthNet: A Variational Approach to Single Image Depth Prediction. International Conference on Learning Representations (ICLR),2023. [PDF]
  10. Ce Liu, Suryansh Kumar, Shuhang Gu, Radu Timofte and Luc Van Gool. Single image depth prediction made better: A multivariate Gaussian take. IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2023. [PDF]
  11. Xiaotao Hu, Jun Xu, Shuhang Gu, Ming-Ming Cheng and Li Liu. Restore globally, refine locally: A mask-guided scheme to accelerate super-resolution networks. European Conference on Computer Vision (ECCV),2022. [PDF]
  12. Yawei Li, Kamil Adamczewski, Wen Li, Shuhang Gu, Radu Timofte and Luc Van Gool. Revisiting random channel pruning for neural network compression. IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2022. [PDF]
  13. Yawei Li, Wen Li, Martin Danelljan, Kai Zhang, Shuhang Gu, Luc Van Gool and Radu Timofte. The heterogeneity hypothesis: Finding layer-wise differentiated network architectures. IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2021. [PDF]
  14. Jingyun Liang, Kai Zhang, Shuhang Gu, Luc Van Gool and Radu Timofte. Flow-based kernel prior with application to blind super-resolution. IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2021. [PDF]
  15. Yunxuan Wei*, Shuhang Gu*, Yawei Li, and Longcun Jin. Unsupervised Real-world Image Super Resolution via Domain Distance Aware Training. IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2021. [PDF][Code] (* Equal Contribution.)
  16. Kangning Liu*, Shuhang Gu*, Andres Romero and Radu Timofte. Unsupervised Multimodal Video-to-Video Translation via Self-Supervised Learning. IEEE/CVF Winter Conference on Applications of Computer Vision (WACV),2021. [Arxiv] (* Equal Contribution.)
  17. Yawei Li, Shuhang Gu, Kai Zhang, Luc Van Gool and Radu Timofte. DHP: Differentiable Meta Pruning via HyperNetworks. European Conference on Computer Vision (ECCV),2020. [PDF]
  18. Jin Xiao*, Shuhang Gu* and Lei Zhang. Multi-domain Learning for Accurate and Few-shot Color Constancy. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020. [PDF] (*Equal contribution)
  19. Yawei Li, Shuhang Gu, Luc Van Gool and Radu Timofte. Group Sparsity: The Hinge Between Filter Pruning and Decomposition for Network Compression. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020.
  20. Shuhang Gu, Yawei Li, Luc Van Gool and Radu Timofte. Self-Guided Network for Fast Image Denoising. IEEE International Conference on Computer Vision (ICCV), 2019. [Code]
  21. Shuhang Gu, Wen Li, Luc Van Gool and Radu Timofte. Fast Image Restoration with Multi-bin Trainable Linear Units. IEEE International Conference on Computer Vision (ICCV), 2019. [Code]
  22. Yawei Li*, Shuhang Gu*, Luc Van Gool and Radu Timofte. Learning Filter Basis for Neural Network Compression. IEEE International Conference on Computer Vision (ICCV), 2019. (* Equal Contribution.)
  23. Manuel Fritsche, Shuhang Gu and Radu Timofte. Frequency Separation for Real-World Super-Resolution. Advances in Image Manipulation workshop (ICCV workshop), 2019. (Winner of AIM challenge on Real-worl Image Super Resolution.)
  24. Minghan Li, Qi Xie, Qian Zhao, Wei Wei, Shuhang Gu, Jing Tao and Deyu Meng. Video Rain Streak Removal by Multiscale Convolutional Sparse Coding. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018.
  25. Mu Li, Wangmeng Zuo, Shuhang Gu, Debin Zhao and David Zhang. Learning Convolutional Networks for Content-weighted Image Compression. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018.
  26. Shuhang Gu, Deyu Meng, Wangmeng Zuo and Lei Zhang. Joint Convolutional Analysis and Synthesis Sparse Representation for Single Image Layer Separation. IEEE International Conference on Computer Vision (ICCV), 2017.
  27. Shuhang Gu, Wangmeng Zuo, Shi Guo, Yunjin Chen, Chongyu Chen and Lei Zhang. Learning Dynamic Guidance for Depth Image Enhancement. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017.
  28. Kai Zhang, Wangmeng Zuo, Shuhang Gu and Lei Zhang. Learning Deep CNN Denoiser Prior for Image Restoration. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017.
  29. Qi Xie, Qian Zhao, Deyu Meng, Zhongben Xu, Shuhang Gu, Wangmeng Zuo and Lei Zhang. Multispectral Images Denoising by Intrinsic Tensor Sparsity Regularization. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016.
  30. Keze Wang, Liang Lin, Wangmeng Zuo, Shuhang Gu and Lei Zhang. Dictionary Pair Classifier Driven Convolutional Neural Networks for Object Detection. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016.
  31. Shuhang Gu, Wangmeng Zuo, Qi Xie, Deyu Meng, Xiangchu Feng and Lei Zhang. Convolutional Sparse Coding for Image Super-resolution. IEEE International Conference on Computer Vision (ICCV), 2015.
  32. Wangmeng Zuo, Dongwei Ren, Shuhang Gu, Liang Lin and Lei Zhang. Discriminative learning of iteration-wise priors for blind deconvolution. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015.
  33. Shuhang Gu, Lei Zhang, Wangmeng Zuo and Xiangchu Feng. Projective dictionary pair learning for pattern classification. Neural Information Processing Systems (NIPS), 2014.
  34. Shuhang Gu, Lei Zhang, Wangmeng Zuo and Xiangchu Feng. Weighted Nuclear Norm Minimization with Application to Image Denoising. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2014.

 

Honors

  • Winner of AIM 2019 Challenge on Real-World Image Super-Resolution 2019

Students Supervised

Master Thesis Projects

  1. Xiaotang Du, 2020.
  2. Manuel Fritsche, 2019.
  3. Kangning Liu, 2019, now PhD student at NYU.
  4. Dario Fuoli, 2019, now PhD student at ETH.

 

 

Academic Service

Workshop and Tutorial Co-organizer

From Image Restoration to Enhancement and Beyond tutorial (FIRE 2019).

New Trends in Image Restoration and Enhancement workshop (NTIRE workshop 2018-2020).

Advanced Image Manipulation workshop (AIM workshop 2019, 2020).


Journal Reviewer

International Journal on Computer Vision

SIAM Journal on Imaging Sciences

IEEE Transactions on Pattern Analysis and Machine Intelligence

IEEE Transactions on Neural Networks and Learning Systems

IEEE Transactions on Computational Imaging

IEEE Transactions on Image Processing

IEEE Transactions on Circuits and Systems for Video Technology

IEEE Transactions on Multimedia

Pattern Recognition


Conference Reviewer

NeurIPS, CVPR, ICCV, ECCV, SIGKDD, AAAI, IJCAI, ACCV

Collaborators