Xuhai Chen

I'm currently pursuing my Master's degree at Zhejiang University in China and expect to graduate in 2025. My advisor is Professor Yong Liu. I've conducted research in image super-resolution and anomaly detection and will continue to maintain these works in the future. Currently, I'm mainly focused on generative tasks, particularly in 3D and 4D.

Life is meant to be experienced.

Email / Scholar / Github / CV

Awards

[2023.06]: CVPR 2023 workshop VAND Challenge: Winner in the Zero-shot Track, Honorable Mention in the Few-shot Track.

Papers

	Better "CMOS" Produces Clearer Images: Learning Space-Variant Blur Estimation for Blind Image Super-Resolution Xuhai Chen, Jiangning Zhang, Chao Xu, Yabiao Wang, Chengjie Wang, Yong Liu CVPR, 2023 paper / github / bibtex Estimating space-variant blur degradation with the help of semantic information.
	A Zero-/Few-Shot Anomaly Classification and Segmentation Method for CVPR 2023 VAND Workshop Challenge Tracks 1&2: 1st Place on Zero-shot AD and 4th Place on Few-shot AD Xuhai Chen, Yue Han, Jiangning Zhang arXiv, 2023 paper / github / bibtex Technical report for the VAND challenge at the 2023 CVPR workshop.
	CLIP-AD: A Language-Guided Staged Dual-Path Model for Zero-shot Anomaly Detection Xuhai Chen, Jiangning Zhang, Guanzhong Tian, Haoyang He, Wuhao Zhang, Yabiao Wang, Chengjie Wang, Yong Liu arXiv, 2023 paper / github / bibtex Adapt the CLIP model for anomaly segmentation by merely fine-tuning a linear layer, and explain the text prompts design from a distributional perspective.
	Exploring Plain ViT Reconstruction for Multi-class Unsupervised Anomaly Detection Jiangning Zhang, Xuhai Chen, Yabiao Wang, Chengjie Wang, Yong Liu, Xiangtai Li, Ming-Hsuan Yang, Dacheng Tao arXiv, 2023 paper / github / bibtex Construct a reverse distillation architecture for multi-class anomaly detection using plain ViT.