| 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 30 (1), 36-47, 2020 | 369 | 2020 |
| Uncertainty-aware blind image quality assessment in the laboratory and wild W Zhang, K Ma, G Zhai, X Yang IEEE Transactions on Image Processing 30, 3474-3486, 2021 | 131 | 2021 |
| Learning to blindly assess image quality in the laboratory and wild W Zhang, K Ma, G Zhai, X Yang 2020 IEEE International Conference on Image Processing (ICIP), 111-115, 2020 | 50 | 2020 |
| 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 45 (3), 2864 …, 2023 | 35 | 2023 |
| 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 32 (9), 5944-5958, 2022 | 35 | 2022 |
| 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 31 (9), 3469 …, 2021 | 28 | 2021 |
| Task-specific normalization for continual learning of blind image quality models W Zhang, K Ma, G Zhai, X Yang arXiv preprint arXiv:2107.13429, 2021 | 15 | 2021 |
| 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, 1-10, 2017 | 15 | 2017 |
| Blind image quality assessment in multiple bandpass and redundancy domains Y Ma, W Zhang, J Yan, C Fan, W Shi Digital Signal Processing 80, 37-47, 2018 | 11 | 2018 |
| Blind image quality assessment based on natural redundancy statistics J Yan, W Zhang, T Feng Computer Vision–ACCV 2016: 13th Asian Conference on Computer Vision, Taipei …, 2017 | 7 | 2017 |
| Hierarchical features fusion for image aesthetics assessment W Zhang, G Zhai, X Yang, J Yan 2019 IEEE international conference on image processing (ICIP), 3771-3775, 2019 | 5 | 2019 |
| 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, 103004, 2021 | 4 | 2021 |
| Blind image quality assessment via vision-language correspondence: A multitask learning perspective W Zhang, G Zhai, Y Wei, X Yang, K Ma Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 3 | 2023 |
| 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 Advances in Neural Information Processing Systems 35, 2916--2929, 2022 | 3 | 2022 |
| 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 27 (2), 023037-023037, 2018 | 3 | 2018 |
| 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 13 (5), 1729881416669486, 2016 | 3 | 2016 |
| 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 8, 158585-158599, 2020 | 2 | 2020 |
| 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 28 (1), 013041-013041, 2019 | 2 | 2019 |
| Learning a Blind Quality Evaluator for UGC Videos in Perceptually Relevant Domains B Li, W Zhang, M Tian, J Jiang, G Zhai, X Wang 2022 IEEE International Conference on Multimedia and Expo (ICME), 1-6, 2022 | 1 | 2022 |
| 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 49 (08), 40 - 45, 2021 | 1 | 2021 |
Kede MaAssistant Professor of Computer Science, City University of Hong KongVerified email at cityu.edu.hk
