Xiangyu Xu

I am a full Professor at Xi'an Jiaotong University. I work on computer vision and machine learning. I got my Bachelor degrees from Tsinghua University and Peking University. I did my PhD at Tsinghua University and my Postdoc at Carnegie Mellon University.

I am looking for PhD, Master, and Undergraduate students and Postdocs to join my lab. Please drop me an email if you are interested.

Email / Bio / Google Scholar

Selected Publications

I'm interested in computer vision, machine learning, and image processing.

	Instant3D: Instant Text-to-3D Generation Ming Li, Pan Zhou, Jia-Wei Liu, Jussi Keppo, Min Lin, Shuicheng Yan, Xiangyu Xu^✉ arXiv, 2023 Paper \| Project Text-to-3D generation without per-prompt training, taking only under a second.
	Progressive Text-to-3D Generation for Automatic 3D Prototyping Han Yi, Zhedong Zheng, Xiangyu Xu, Tat-seng Chua arXiv, 2023 Paper \| Project A progressive strategy that learns text-to-3D in a coarse-to-fine manner
	NU-MCC: Multiview Compressive Coding with Neighborhood Decoder and Repulsive UDF Stefan Lionar, Xiangyu Xu^✉, Min Lin, Gim Hee Lee Conference on Neural Information Processing Systems (NeurIPS), 2023 Paper \| Project We achieve new SOTA for single-view 3D reconstruction on CO3D.
	Towards Garment Sewing Pattern Reconstruction from a Single Image Lijuan Liu, Xiangyu Xu, Zhijie Lin, Jiabin Liang, Shuicheng Yan ACM Transactions on Graphics (SIGGRAPH Asia), 2023 Paper \| Code \| New Scientist We present the first solution for sewing pattern reconstruction from a single image.
	STPrivacy: Spatio-Temporal Privacy-Preserving Action Recognition Ming Li, Xiangyu Xu, Hehe Fan, Pan Zhou, Jun Liu, Jia-Wei Liu, Jiahe Li, Jussi Keppo, Mike Zheng Shou, Shuicheng Yan International Conference on Computer Vision (ICCV), 2023 Paper \| Code We explore privacy-preserving action recognition from a spatio-temporal perspective.
	Cylin-Painting: Seamless 360° Panoramic Image Outpainting and Beyond Kang Liao, Xiangyu Xu, Chunyu Lin, Wenqi Ren, Yunchao Wei, Yao Zhao IEEE Transactions on Image Processing (TIP), 2023 Paper \| Code We propose a cylinder-style convolution for completing panoramic views.
	GLEAN: Generative Latent Bank for Image Super-Resolution and Beyond Kelvin C.K. Chan, Xiangyu Xu, Xintao Wang, Jinwei Gu, and Chen Change Loy IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022 Paper \| Code We develop a lighter version of GLEAN.
	Geometry-Guided Progressive NeRF for Generalizable and Efficient Neural Human Rendering Mingfei Chen, Jianfeng Zhang, Xiangyu Xu^✉, Lijuan Liu, Yujun Cai, Jiashi Feng, Shuicheng Yan European Conference on Computer Vision (ECCV), 2022 Paper \| Code We present an SMPL-based NeRF for multi-view human synthesis, which is efficient and generalizable to unseen subjects and sparse views.
	Video Frame Interpolation Transformer Zhihao Shi, Xiangyu Xu^✉*, Xiaohong Liu, Jun Chen, Ming-Hsuan Yang Computer Vision and Pattern Recognition Conference (CVPR)*, 2022 Paper \| Code We present the first Transformer architecture for video frame interpolation.
	Investigating Tradeoffs in Real-World Video Super-Resolution Kelvin C.K. Chan, Shangchen Zhou, Xiangyu Xu, and Chen Change Loy Computer Vision and Pattern Recognition Conference (CVPR), 2022 Paper \| Code Several useful techniques for real-world video super-resolution.
	BasicVSR++: Improving Video Super-Resolution with Enhanced Propagation and Alignment Kelvin C.K. Chan, Shangchen Zhou, Xiangyu Xu, and Chen Change Loy Computer Vision and Pattern Recognition Conference (CVPR), 2022 Paper \| Project Winner algorithm for video enhancement challenges in NTIRE 2021.
	3D Human Texture Estimation from a Single Image with Transformers Xiangyu Xu, Chen Change Loy International Conference on Computer Vision (ICCV), 2021 (Oral Presentation) Paper \| Code \| Project We present a Transformer for 3D human texture estimation from a single image.
	3D Human Pose, Shape and Texture from Low-Resolution Images and Videos Xiangyu Xu, Hao Chen, Francesc Moreno-Noguer, Laszlo A. Jeni, and Fernando De la Torre IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021 Paper \| Code We extend RSC-Net to videos and propose a human texture estimation model.
	GLEAN: Generative Latent Bank for Large-Factor Image Super-Resolution Kelvin C.K. Chan, Xintao Wang, Xiangyu Xu, Jinwei Gu, and Chen Change Loy Computer Vision and Pattern Recognition Conference (CVPR), 2021 (Oral Presentation) Paper \| Project We use StyleGAN for image super-resolution.
	Super-Resolution Capacitive Touchscreens Sven Mayer, Xiangyu Xu, and Chris Harrison ACM Conference on Human Factors in Computing Systems (CHI), 2021 Paper \| YouTube For the first time, super-resolution is applied to human-computer interaction.
	Exploiting Raw Images for Real-Scene Super-Resolution Xiangyu Xu, Yongrui Ma, Wenxiu Sun, and Ming-Hsuan Yang IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020 Paper \| Project \| Code We improve the RawSR architecture and extend it to image dehazing and depth upsampling.
	3D Human Shape and Pose from a Single Low-Resolution Image with Self-Supervised Learning Xiangyu Xu, Hao Chen, Francesc Moreno-Noguer, Laszlo A. Jeni, and Fernando De la Torre European Conference on Computer Vision (ECCV), 2020 Paper \| Project \| Code We propose a new algorithm for 3D human shape and pose estimation that is robust to low-resolution input.
	Learning Spatial and Spatio-Temporal Pixel Aggregations for Image and Video Denoising Xiangyu Xu, Muchen Li, Wenxiu Sun, and Ming-Hsuan Yang IEEE Transactions on Image Processing (TIP), 2020 Paper \| Code We propose spatio-temporal deformable convolution kernels for image and video denoising.
	Learning Factorized Weight Matrix for Joint Filtering Xiangyu Xu, Yongrui Ma, Wenxiu Sun International Conference on Machine Learning (ICML), 2020 (Long Talk) Paper \| Project We propose deep Robust PCA for joint image filtering.
	Quadratic Video Interpolation Xiangyu Xu, Siyao Li, Wenxiu Sun, Qian Yin, and Ming-Hsuan Yang Conference on Neural Information Processing Systems (NeurIPS), 2019 (Spotlight) Paper \| Code We present the first nonlinear motion model for image interpolation. The method won the Champion of AIM 2019 video interpolation challenge.
	Towards Real Scene Super-Resolution with Raw Images Xiangyu Xu, Yongrui Ma, Wenxiu Sun Computer Vision and Pattern Recognition Conference (CVPR), 2019 Paper \| Code We present the first neural network for raw image based super-resolution. It works very well on real-world input.
	Low-Light Image Enhancement via a Deep Hybrid Network Wenqi Ren, Sifei Liu, Lin Ma, Qianqian Xu, Xiangyu Xu, Xiaochun Cao, Junping Du, Ming-Hsuan Yang IEEE Transactions on Image Processing (TIP), 2019 Paper We present a hybrid structure of CNN and RNN for low-light image enhancement.
	Rendering Portraitures from Monocular Camera and Beyond Xiangyu Xu, Deqing Sun, Sifei Liu, Wenqi Ren, Yu-Jin Zhang, Ming-Hsuan Yang, Jian Sun European Conference on Computer Vision (ECCV), 2018 Paper We present a CRF-based pipeline and a deep neural filter for rendering shallow depth-of-field effect with monocular camera.
	Monocular Depth Estimation with Affinity, Vertical Pooling and Label Enhancement Yukang Gan, Xiangyu Xu*, Wenxiu Sun, Liang Lin European Conference on Computer Vision (ECCV)*, 2018 Paper We propose to incorporate relative features, i.e., affinity, for monocular depth estimation.
	Motion Blur Kernel Estimation via Deep Learning Xiangyu Xu, Jinshan Pan, Yu-Jin Zhang, Ming-Hsuan Yang IEEE Transactions on Image Processing (TIP), 2018 Paper \| Project We present a deep neural network to extract salient edges for blind image deblurring.
	Deep Video Dehazing with Semantic Segmentation Wenqi Ren, Jingang Zhang, Xiangyu Xu, Lin Ma, Xiaochun Cao, Gaofeng Meng, Wei Liu IEEE Transactions on Image Processing (TIP)*, 2018 Paper We exploit a neural network to perform haze removal for videos.
	Learning to Super-Resolve Blurry Face and Text Images Xiangyu Xu, Deqing Sun, Jinshan Pan, Yu-Jin Zhang, Hanspeter Pfister, Ming-Hsuan Yang International Conference on Computer Vision (ICCV), 2017 Paper \| Project We present the first deep neural network for blind image super-resolution.

Professional Services

Area Chair: CVPR 2023, BMVC 2023, CVPR 2024, ICLR 2024
Session Chair: SIGGRAPH Asia 2023
Senior Program Committee: IJCAI 2021, AAAI 2023, AAAI 2024

Students/Interns

Stefan Lionar, PhD (Sea AI Lab and NUS, 2023-present)
Ming Li, Intern (Sea AI Lab, 2023-present)
Hao Chen, Master (CMU, 2019-2020), Now: PhD at CMU
Muchen Li, Intern (SenseTime, 2018-2019), Now: PhD at UBC
Yongrui Ma, Intern (SenseTime, 2018-2019), Now: PhD at CUHK

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