Weixia Zhang
Cited by
Cited by
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
李博文, 田猛, 张维夏, 王先培
华中科技大学学报 49 (08), 40 - 45, 2021
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