Publications

For the most up-to-date record, please also see my Google Scholar and ResearchGate profiles.

2026

1. Unveiling the Modular Design of Text-to-Video Quality Assessment
   B. Zheng, W. Zhang, G. Zhai, X. Yang.
   IEEE Transactions on Circuits and Systems for Video Technology, 2026.

2. Robust Low-Light Image Enhancement In the Wild via Data Synthesis and Generative Diffusion Prior
   Z. Wang, Q. Lin, F. Liu, W. Zhang, W. Zhou.
   Pattern Recognition, 2026.

3. QualiRAG: Retrieval-Augmented Generation for Visual Quality Understanding
   L. Cao, W. Sun, W. Zhang, X. Zhu, K. Zhang, J. Jia, D. Zhu, G. Zhai, X. Min.
   arXiv preprint, 2026.

2025

1. Evaluating Perceptual Color Preferences in Smartphone Photography: Dataset and Challenges
   Z. Wang, W. Zhang, W. Zhou, X. Liu, G. Zhai, P. Le Callet.
   ACM Multimedia, 2025.

2. VQualA 2025 Challenge on GenAI-Bench AIGC Video Quality Assessment: Methods and Results
   Y. Chen, H. Wang, P. Xiao, Y. Ding, E. Liu, C. W. Zhou, B. Li, J. Huang, J. Wang, et al.
   ICCV Workshops, 2025.

3. Learning from Model Rankings Improves Blind Super-Resolution Image Quality Assessment
   J. Chen, P. Cao, G. Zhai, X. Yang, W. Zhang.
   IEEE SMC, 2025.

4. VQAThinker: Exploring Generalizable and Explainable Video Quality Assessment via Reinforcement Learning
   L. Cao, W. Sun, W. Zhang, X. Zhu, J. Jia, K. Zhang, D. Zhu, G. Zhai, X. Min.
   arXiv preprint, 2025.

5. Machine Learning–Based Prediction of Large-for-Gestational-Age Infants in Mothers With Gestational Diabetes Mellitus
   M. Kang, C. Zhu, M. Lai, J. Weng, Y. Zhuang, H. He, Y. Qiu, Y. Wu, Z. Qi, et al.
   The Journal of Clinical Endocrinology & Metabolism, 2025.

6. Artificial Intelligence Algorithm for Preoperative Prediction of FIGO Stage in Ovarian Cancer Based on Clinical Features Integrated 18F-FDG PET/CT Metabolic and Radiomics Features
   S. Xu, C. Zhu, M. Wu, S. Gu, Y. Wu, S. Cheng, C. Wang, Y. Zhang, W. Zhang, et al.
   Journal of Cancer Research and Clinical Oncology, 2025.

7. When No-Reference Image Quality Models Meet MAP Estimation in Diffusion Latents
   W. Zhang, D. Li, G. Zhai, X. Yang, K. Ma.
   arXiv preprint, 2025.

8. VQualA 2025 Document Image Quality Assessment Challenge
   F. Huang, X. Min, Z. Ma, X. Liu, C. W. Zhou, G. Zhai, J. Gao, R. Liu, Y. Peng, et al.
   ICCV Workshops, 2025.

9. VQualA 2025 Challenge on Visual Quality Comparison for Large Multimodal Models: Methods and Results
   H. Zhu, H. Wu, Z. Zhang, L. Zhu, Y. Li, P. Chen, S. Wang, C. W. Zhou, L. Cao, et al.
   ICCV Workshops, 2025.

10. VQualA 2025 Challenge on Image Super-Resolution Generated Content Quality Assessment: Methods and Results
    Y. Li, X. Li, C. W. Zhou, S. Xing, H. Amirpour, X. Hao, G. Yue, B. Zhao, W. Liu, et al.
    ICCV Workshops, 2025.

11. VQualA 2025 Challenge on Engagement Prediction for Short Videos: Methods and Results
    D. Li, S. Ma, H. Hua, W. Li, J. Wang, C. W. Zhou, F. Guan, X. Li, Z. Yu, Y. Lu, et al.
    ICCV Workshops, 2025.

12. VQualA 2025 Challenge on Face Image Quality Assessment: Methods and Results
    S. Ma, W.-T. Chen, Q. Gao, J. Wang, C. W. Zhou, W. Sun, W. Zhang, L. Cao, J. Jia, et al.
    ICCV Workshops, 2025.

13. Engagement Prediction of Short Videos with Large Multimodal Models
    W. Sun, L. Cao, Y. Cao, W. Zhang, W. Wen, K. Zhang, Z. Chen, F. Lu, X. Min, et al.
    ICCV Workshops, 2025.

14. Efficient Face Image Quality Assessment via Self-training and Knowledge Distillation
    W. Sun, W. Zhang, L. Cao, J. Jia, X. Zhu, D. Zhu, X. Min, G. Zhai.
    ICCV Workshops, 2025.

15. Multi-Dimensional Quality Assessment for UGC Videos via Modular Multi-Modal Vision-Language Models
    W. Zhang, B. Zheng, J. Chen, Z. Wang.
    CVPR Workshops, 2025.

16. NTIRE 2025 XGC Quality Assessment Challenge: Methods and Results
    X. Liu, X. Min, Q. Hu, X. Zhang, J. Guo, G. Zhai, S. Wang, Y. Zhou, L. Liu, J. Li, et al.
    CVPR Workshops, 2025.

17. NTIRE 2025 Challenge on Real-World Face Restoration: Methods and Results
    Z. Chen, J. Wang, K. Liu, J. Gong, L. Sun, Z. Wu, R. Timofte, Y. Zhang, J. Zhang, et al.
    CVPR Workshops, 2025.

2024

1. SR-VQA: Super-Resolution Video Quality Assessment Model
   Y. Cao, W. Sun, W. Zhang, Y. Sun, Z. Jia, Y. Zhu, X. Min, G. Zhai.
   ECCV Workshops, 2024.

2. AIM 2024 Challenge on Video Super-Resolution Quality Assessment: Methods and Results
   I. Molodetskikh, A. Borisov, D. Vatolin, R. Timofte, J. Liu, T. Zhi, Y. Zhang, Y. Li, et al.
   ECCV Workshops, 2024.

3. AIM 2024 Challenge on UHD Blind Photo Quality Assessment
   V. Hosu, M. V. Conde, L. Agnolucci, N. Barman, S. Zadtootaghaj, R. Timofte, et al.
   ECCV Workshops, 2024.

4. Assessing UHD Image Quality from Aesthetics, Distortions, and Saliency
   W. Sun, W. Zhang, Y. Cao, L. Cao, J. Jia, Z. Chen, Z. Zhang, X. Min, G. Zhai.
   ECCV Workshops, 2024.

5. A Comparative Study of Perceptual Quality Metrics for Audio-driven Talking Head Videos
   W. Zhang, C. Zhu, J. Gao, Y. Yan, G. Zhai, X. Yang.
   ICIP, 2024.

6. Q-Align: Teaching LMMs for Visual Scoring via Discrete Text-Defined Levels
   H. Wu, Z. Zhang, W. Zhang, C. Chen, L. Liao, C. Li, Y. Gao, A. Wang, E. Zhang, et al.
   ICML, 2024.

7. Dual-Branch Network for Portrait Image Quality Assessment
   W. Sun, W. Zhang, Y. Jiang, H. Wu, Z. Zhang, J. Jia, Y. Zhou, Z. Ji, X. Min, W. Lin, et al.
   arXiv preprint, 2024.

8. AIS 2024 Challenge on Video Quality Assessment of User-Generated Content: Methods and Results
   M. V. Conde, S. Zadtootaghaj, N. Barman, R. Timofte, C. He, Q. Zheng, R. Zhu, et al.
   CVPR Workshops, 2024.

9. Deep Portrait Quality Assessment: A NTIRE 2024 Challenge Survey
   N. Chahine, M. V. Conde, D. Carfora, G. Pacianotto, B. Pochon, S. Ferradans, et al.
   CVPR Workshops, 2024.

10. AIGIQA-20K: A Large Database for AI-Generated Image Quality Assessment
    C. Li, T. Kou, Y. Gao, Y. Cao, W. Sun, Z. Zhang, Y. Zhou, Z. Zhang, W. Zhang, et al.
    CVPR, 2024.

11. Task-Specific Normalization for Continual Learning of Blind Image Quality Models
    W. Zhang, K. Ma, G. Zhai, X. Yang.
    IEEE Transactions on Image Processing, 2024.

2023

1. LLIEFormer: A Low-Light Image Enhancement Transformer Network with a Degraded Restoration Model
   X. Yi, Y. Wang, Y. Zhao, J. Yan, W. Zhang.
   ICIP, 2023.

2. Continual Learning for Blind Image Quality Assessment
   W. Zhang, D. Li, C. Ma, G. Zhai, X. Yang, K. Ma.
   IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023.

3. 基于神经网络的生成式三维数字人研究综述：表示、渲染与学习
   晏轶超，程宇豪，陈琢，彭乙骢，吴思婧，张维天，李俊杰，李逸轩，高景南，等。
   中国科学：信息科学, 2023.

4. Blind Image Quality Assessment via Vision-Language Correspondence: A Multitask Learning Perspective
   W. Zhang, G. Zhai, W. Ying, X. Yang, K. Ma.
   CVPR, 2023.

2022

1. Perceptual Attacks of No-Reference Image Quality Models with Human-in-the-Loop
   W. Zhang, D. Li, X. Min, G. Zhai, G. Guo, X. Yang, K. Ma.
   NeurIPS, 2022.

2. Learning a Blind Quality Evaluator for UGC Videos in Perceptually Relevant Domains
   B. Li, W. Zhang, M. Tian, J. Jiang, G. Zhai, X. Wang.
   ICME, 2022.

3. Blindly Assess Quality of In-the-Wild Videos via Quality-aware Pre-training and Motion Perception
   B. Li, W. Zhang, M. Tian, G. Zhai, X. Wang.
   IEEE Transactions on Circuits and Systems for Video Technology, 2022.

2021

1. Language-Guided Navigation via Cross-Modal Grounding and Alternate Adversarial Learning
   W. Zhang, C. Ma, Q. Wu, X. Yang.
   IEEE Transactions on Circuits and Systems for Video Technology, 2021.

2. 基于多层级信息稀疏表征的盲图像质量评价
   李博文，田猛，张维夏，王先培。
   华中科技大学学报（自然科学版）, 2021.

3. Uncertainty-Aware Blind Image Quality Assessment in the Laboratory and Wild
   W. Zhang, K. Ma, G. Zhai, X. Yang.
   IEEE Transactions on Image Processing, 2021.

4. Learning to Predict the Quality of Distorted-then-Compressed Images via a Deep Neural Network
   B. Li, M. Tian, W. Zhang, H. Yao, X. Wang.
   Journal of Visual Communication and Image Representation, 2021.

2020

1. Dual Head Network for No-Reference Quality Assessment Towards Realistic Night-Time Images
   B. Li, X. Wang, W. Zhang, M. Tian, H. Yao.
   IEEE Access, 2020.

2. Learning to Blindly Assess Image Quality in the Laboratory and Wild
   W. Zhang, K. Ma, G. Zhai, X. Yang.
   ICIP, 2020.

3. Blind Image Quality Assessment Using a Deep Bilinear Convolutional Neural Network
   W. Zhang, K. Ma, J. Yan, D. Deng, Z. Wang.
   IEEE Transactions on Circuits and Systems for Video Technology, 2020.

2019

1. Hierarchical Features Fusion for Image Aesthetics Assessment
   W. Zhang, G. Zhai, X. Yang, J. Yan.
   ICIP, 2019.

2. No-Reference Quality Assessment for Contrast-Altered Images Using an End-to-End Deep Framework
   S. Hu, J. Yan, W. Zhang, D. Deng.
   Journal of Electronic Imaging, 2019.

2018

1. Blind Image Quality Assessment in Multiple Bandpass and Redundancy Domains
   Y. Ma, W. Zhang, J. Yan, C. Fan, W. Shi.
   Digital Signal Processing, 2018.

2. Predicting Perceptual Quality of Images in Realistic Scenario Using Deep Filter Banks
   W. Zhang, J. Yan, S. Hu, Y. Ma, D. Deng.
   Journal of Electronic Imaging, 2018.

3. 基于多通道特征聚合的盲图像质量评价
   张维夏，邓德祥，颜佳。
   华中科技大学学报（自然科学版）, 2018.

2017

1. Refining Deep Convolutional Features for Improving Fine-Grained Image Recognition
   W. Zhang, J. Yan, W. Shi, T. Feng, D. Deng.
   EURASIP Journal on Image and Video Processing, 2017.

2016

1. Blind Image Quality Assessment Based on Natural Redundancy Statistics
   J. Yan, W. Zhang, T. Feng.
   Asian Conference on Computer Vision, 2016.

2. Sparse Representation of Salient Regions for No-Reference Image Quality Assessment
   T. Feng, D. Deng, J. Yan, W. Zhang, W. Shi, L. Zou.
   International Journal of Advanced Robotic Systems, 2016.

Thesis

张维夏. 基于特征聚合和数据驱动的盲图像质量评价. [CNKI]