Zhiyuan You | 尤志远

Ph.D. Candidate

The Chinese University of Hong Kong

zhiyuanyou@foxmail.com | zhiyuanyou.ai@gmail.com

Zhiyuan You

Biography

I am a Ph.D. candidate at Multimedia Laboratory (MMLab), The Chinese University of Hong Kong (CUHK). I am supervised by Prof. Tianfan Xue and Prof. Chao Dong. I also work closely with Dr. Jinjin Gu.

Prior to that, I received my M.Eng. from Shanghai Jiao Tong University (SJTU) in 2023, supervised by Prof. Xinyi Le and Prof. Yu Zheng, and my B.Eng. from the same university in 2020.

I previously conducted research at several leading institutions, including ByteDance Seed, Adobe, Shanghai AI Lab, Horizon Robotics, and SenseTime.

My current research interest mainly lies in generation models, multi-modal systems, vision-centric agent, and low-level vision.

News

[2026.07]  One paper to appear in ACM MM 2026.
[2026.05]  One paper to appear in ICML 2026 (Oral).
[2026.03]  One paper to appear in ACL 2026.
[2026.03]  One paper to appear in PR.
[2026.02]  Three papers (One Findings Workshop) to appear in CVPR 2026.
[2025.11]  One paper to appear in TIP.
[2025.11]  End of my internship at Adobe — heartfelt thanks to all the teams.
[2025.09]  Two papers (One Datasets & Benchmarks Track) to appear in NeurIPS 2025.
[2025.08]  One paper to appear in TOG, SIGGRAPH Asia 2025 (Journal Track).
[2025.07]  We win the Championship 🏆 in the VQualA 2025 DIQA Challenge (ICCV 2025 Workshop).
[2025.03]  One paper to appear in TPAMI.
[2025.02]  Two papers to appear in CVPR 2025 (One Highlight). See you in Nashville.
[2025.01]  One paper to appear in ICLR 2025.
[2024.12]  One paper to appear in AAAI 2025 (Oral).
[2024.09]  One paper to appear in NeurIPS 2024 (Spotlight).
[2024.08]  One paper to appear in TMLR.
[2024.07]  One paper to appear in ECCV 2024. See you in Milan.
[2023.08]  I become a Ph.D. student at MMLab in The Chinese University of Hong Kong.
[2023.03]  I graduate and receive my Master's degree from Shanghai Jiao Tong University.
[2022.09]  One paper to appear in NeurIPS 2022 (Spotlight).
[2022.09]  One paper to appear in ICONIP 2023 (Oral).
[2022.08]  One paper to appear in WACV 2023 (Early Accept).
[2021.12]  One paper to appear in NN.
[2020.07]  I graduate and receive my Bachelor's degree from Shanghai Jiao Tong University.

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Publications

*: Equal Contribution, †: Corresponding Author

Generative Image Processing / LLM & MLLM Applications / Low-level Vision / Anomaly Detection / Misc / All
PhotoAgent
PhotoAgent: Agentic Photo Editing with Exploratory Visual Aesthetic Planning
Mingde Yao, Zhiyuan You, King-Man Tam, Menglu Wang, and Tianfan Xue†
International Conference on Machine Learning (ICML), 2026, Oral

[Project Page] [Paper] [Code]

We propose PhotoAgent, an autonomous photo editing agent that performs multi-step aesthetic planning and refinement to transform images with minimal user input.
RouteMoA
RouteMoA: Dynamic Routing without Pre-Inference Boosts Efficient Mixture-of-Agents
Jize Wang, Han Wu, Zhiyuan You, Yiming Song, Yijun Wang, Zifei Shan, Yining Li, Songyang Zhang, Xinyi Le†, Cailian Chen†, Xinping Guan, Dacheng Tao
Annual Meeting of the Association for Computational Linguistics (ACL), 2026

[Paper] [Code]

We propose RouteMoA, an efficient mixture-of-agents framework with dynamic routing. RouteMoA uses a lightweight scorer to predict coarse-grained performance, finding high-potential candidates without inference.
DA-VAE
DA-VAE: Plug-in Latent Compression for Diffusion via Detail Alignment
Xin Cai, Zhiyuan You, Zhoutong Zhang, Tianfan Xue†
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2026

[Project Page] [Paper] [Code]

We introduce Detail-Aligned VAE (DA-VAE), a method that increases the compression ratio of a pretrained VAE while requiring only lightweight adaptation for the pretrained diffusion backbone.
PhotoFramer
PhotoFramer: Multi-modal Image Composition Instruction
Zhiyuan You, Ke Wang, He Zhang, Xin Cai, Jinjin Gu, Tianfan Xue†, Chao Dong†, Zhoutong Zhang
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2026

[Project Page] [Paper] [Code]

We introduce PhotoFramer, a multi-modal composition instruction framework, to provide composition guidance. Given a poorly composed image, PhotoFramer first describes how to improve the composition in natural language and then generates a well-composed example image.
Generative Image Restoration Study
How Far Have We Gone in Generative Image Restoration? A Study on Its Capability, Limitations and Evaluation Practices
Xiang Yin, Jinfan Hu, Zhiyuan You, Kainan Yan, Yu Tang, Chao Dong, Jinjin Gu
IEEE Conference on Computer Vision and Pattern Recognition Workshop (CVPRW), 2026

[Project Page] [Paper] [Code]

We present a large-scale and multi-dimensional study on generative image restoration, covering diverse architectures, revealing critical performance disparities.
Deraining generalization
Revisiting the Generalization Problem of Low-level Vision Models Through the Lens of Image Deraining
Jinfan Hu*, Zhiyuan You*, Jinjin Gu, Kaiwen Zhu, Tianfan Xue, Chao Dong†
Pattern Recognition (PR), 2026

[Paper]

We investigate the underlying mechanism of the generalization failure to unseen degradations in low-level vision, and show that the key to better generalization lies in guiding the network to learn the image content rather than the degradation.
RadarQA
RadarQA: Multi-modal Quality Analysis of Weather Radar Forecasts
Xuming He*, Zhiyuan You*, Junchao Gong, Couhua Liu, Xiaoyu Yue, Peiqin Zhuang, Wenlong Zhang†, Lei Bai†
Neural Information Processing Systems (NeurIPS), 2025

[Paper] [Code] [Data]

We introduce an MLLM-based weather forecast quality analysis method, RadarQA, integrating key physical attributes with detailed assessment reports.
ReinAD
ReinAD: Towards Real-world Industrial Anomaly Detection with a Comprehensive Contrastive Dataset
Xu Wang, Jingyuan Zhuo, Zhiyuan You, Zhiyu Tan, Yikuan Yu, Siyu Wang, Xinyi Le†
Neural Information Processing Systems (NeurIPS), 2025, Datasets & Benchmarks Track

[Project Page] [Paper] [Code] [Data]

We introduce ReinAD dataset, a comprehensive, contrast-based, fine-grained, unaligned, and large-scale dataset towards real-world industrial anomaly detection.
HYPIR
Harnessing Diffusion-Yielded Score Priors for Image Restoration
Xinqi Lin, Fanghua Yu, Jinfan Hu, Zhiyuan You, Wu Shi, Jimmy S. Ren, Jinjin Gu†, Chao Dong†
ACM Transactions on Graphics (TOG), ACM SIGGRAPH Asia, 2025, Journal Track

[Project Page] [Paper] [Code] [Online App] [CCTV News (央视新闻直播间报道)]

We introduce HYPIR, a simple yet powerful paradigm: fine-tuning a pre-trained diffusion model with adversarial (GAN) loss — no diffusion sampling, no extra adapters, achieving an unprecedented balance of speed, fidelity, and quality.
DeQA-Doc
DeQA-Doc: Adapting DeQA-Score to Document Image Quality Assessment
Junjie Gao, Runze Liu, Yingzhe Peng, Shujian Yang, Jin Zhang, Kai Yang†, Zhiyuan You
IEEE International Conference on Computer Vision Workshop (ICCVW), 2025

[Paper] [Code]

Our DeQA-Doc wins the Championship 🏆 in the VQualA 2025 DIQA (Document Image Quality Assessment) Challenge, ICCV 2025 Workshop.
DeQA-Score
Teaching Large Language Models to Regress Accurate Image Quality Scores using Score Distribution
Zhiyuan You, Xin Cai, Jinjin Gu, Tianfan Xue†, Chao Dong†
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2025

[Project Page] [Paper] [Code] [Data]

We introduce DeQA-Score, a distribution-based depicted image quality assessment model for score regression.
UltraFusion
UltraFusion: Ultra High Dynamic Imaging using Exposure Fusion
Zixuan Chen*, Yujin Wang*, Xin Cai, Zhiyuan You, Zheming Lu, Fan Zhang, Shi Guo, Tianfan Xue†
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2025, Highlight, Best Demo Honorable Mention

[Project Page] [GitHub Page] [Paper] [Code] [Demo: HuggingFace / OpenXLab]

We propose UltraFusion, the first exposure fusion technique that can merge input with 9 stops differences.
Causal Effect Maps
Interpreting Low-level Vision Models with Causal Effect Maps
Jinfan Hu, Jinjin Gu, Shiyao Yu, Fanghua Yu, Zheyuan Li, Zhiyuan You, Chaochao Lu, Chao Dong†
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2025

[Paper] [Code]

We propose Causal Effect Map (CEM), a model-agnostic and task-agnostic interpreting method for low-level vision models.
AgenticIR
An Intelligent Agentic System for Complex Image Restoration Problems
Kaiwen Zhu*, Jinjin Gu*, Zhiyuan You, Yu Qiao, Chao Dong†
International Conference on Learning Representations (ICLR), 2025

[Project Page] [Paper] [Code]

We introduce AgenticIR, an LLM-based agentic system that utilize various tools for complex image restoration problems.
SAIL
SAIL: Sample-Centric In-Context Learning for Document Information Extraction
Jinyu Zhang*, Zhiyuan You*, Jize Wang, Xinyi Le†
Association for the Advancement of Artificial Intelligence (AAAI), 2025, Oral

[Paper] [Code]

We introduce SAIL, a sample-centric approach selecting tailored in-context examples for training-free document information extraction.
DepictQA-Wild
Enhancing Descriptive Image Quality Assessment with A Large-scale Multi-modal Dataset
Zhiyuan You, Jinjin Gu, Xin Cai, Zheyuan Li, Kaiwen Zhu, Chao Dong†, Tianfan Xue†
IEEE Transactions on Image Processing (TIP), 2025

[Project Page] [Paper] [Code] [Data]

We introduce DepictQA-Wild, also named Enhanced DepictQA (EDQA), a multi-functional in-the-wild descriptive image quality assessment model.
PhoCoLens
PhoCoLens: Photorealistic and Consistent Reconstruction in Lensless Imaging
Xin Cai, Zhiyuan You, Hailong Zhang, Wentao Liu, Jinwei Gu, Tianfan Xue†
Neural Information Processing Systems (NeurIPS), 2024, Spotlight

[Project Page] [Paper] [Code]

We introduce PhoCoLens, a novel two-stage approach for consistent and photorealistic lensless image reconstruction.
DepictQA
Depicting Beyond Scores: Advancing Image Quality Assessment through Multi-modal Language Models
Zhiyuan You*, Zheyuan Li*, Jinjin Gu*, Zhenfei Yin, Tianfan Xue†, Chao Dong†
European Conference on Computer Vision (ECCV), 2024

[Project Page] [Paper] [Code] [Data]

We introduce DepictQA, leveraging multi-modal large language models, allowing for detailed, language-based, and human-like evaluation of image quality.
MaskMA
MaskMA: Towards Zero-Shot Multi-Agent Decision Making with Mask-Based Collaborative Learning
Jie Liu*, Yinmin Zhang*, Chuming Li, Zhiyuan You, Zhanhui Zhou, Chao Yang, Yaodong Yang†, Yu Liu, Wanli Ouyang
Transactions on Machine Learning Research (TMLR), 2024

[Paper]

We release MaskMA, a masked pretraining framework for multi-agent decision-making.
SAFECount
Few-shot Object Counting with Similarity-Aware Feature Enhancement
Zhiyuan You, Kai Yang, Wenhan Luo, Xin Lu, Lei Cui, Xinyi Le†
Winter Conference on Applications of Computer Vision (WACV), 2023, Early Accept

[Paper] [Code] [Video]

We propose a novel SAFECount block, equipped with a similarity comparison module and a feature enhancement module for few-shot object counting.
UniAD
A Unified Model for Multi-class Anomaly Detection
Zhiyuan You, Lei Cui, Yujun Shen, Kai Yang, Xin Lu, Yu Zheng, Xinyi Le†
Neural Information Processing Systems (NeurIPS), 2022, Spotlight

[Paper] [Code]

We present UniAD that accomplishes anomaly detection for multiple classes with a unified framework.
ADTR
ADTR: Anomaly Detection Transformer with Feature Reconstruction
Zhiyuan You, Kai Yang, Wenhan Luo, Lei Cui, Yu Zheng, Xinyi Le†
International Conference on Neural Information Processing (ICONIP), 2022, Oral

[Paper]

We propose ADTR to apply a transformer to reconstruct pre-trained features for anomaly detection, and propose novel losses to extend ADTR to anomaly-available case (both image-level & pixel-level labeled).
Star identification
An accurate star identification approach based on spectral graph matching for attitude measurement of spacecraft
Zhiyuan You, Junzheng Li, Hongcheng Zhang, Bo Yang, Xinyi Le†
Complex & Intelligent Systems (CAIS), 2022

[Paper] [Code]

My undergraduate thesis and my first first-author paper. We propose a novel star identification approach based on spectral graph matching.
UTRAD
UTRAD: Anomaly detection and localization with u-transformer
Liyang Chen, Zhiyuan You, Nian Zhang, Juntong Xi, Xinyi Le†
Neural Networks (NN), 2022

[Paper] [Code]

We introduce UTRAD, a U-TRansformer based Anomaly Detection framework.

Education

Ph.D. Candidate at Multimedia Laboratory (MMLab) @ The Chinese University of Hong Kong
Aug. 2023 - Current
GPA: 3.82 / 4.0
Advisor: Prof. Tianfan Xue and Prof. Chao Dong
M.Eng. with Honor @ Shanghai Jiao Tong University
Sep. 2020 - Mar. 2023
GPA: 3.76 / 4.0
Advisor: Prof. Xinyi Le and Prof. Yu Zheng
B.Eng. with Honor @ Shanghai Jiao Tong University
Sep. 2016 - Jun. 2020
GPA: 89.36 / 100, Ranking: 5 / 148
Advisor: Prof. Xinyi Le

Experience

Research Intern @ ByteDance Seed
Current
Team: Seedance Team
Mentor: Dr. Zhaoyang Huang and Dr. Feng Wang
Research Scientist Intern @ Adobe
Jul. 2025 - Nov. 2025
Team: Marc Levoy's NextCam Team
Mentor: Dr. Zhoutong Zhang, Dr. Ke Wang, and Dr. He Zhang
Research Intern @ Shanghai Artificial Intelligence Laboratory
May. 2024 - Apr. 2025
Mentor: Prof. Chao Dong
Research Intern @ Horizon Robotics
Nov. 2022 - Mar. 2023
Mentor: Dr. Yuelong Yu
Research Intern @ SenseTime
Dec. 2020 - Nov. 2022
Mentor: Mr. Kai Yang

Academic Service

Awards