TOPIQ: A Top-Down Approach From Semantics to Distortions for Image Quality Assessment

Author:

Chen Chaofeng1ORCID,Mo Jiadi1,Hou Jingwen2ORCID,Wu Haoning1ORCID,Liao Liang1ORCID,Sun Wenxiu3ORCID,Yan Qiong3,Lin Weisi2ORCID

Affiliation:

1. S-Lab, Nanyang Technological University (NTU), Jurong West, Singapore

2. School of Computer Science and Engineering, Nanyang Technological University (NTU), Jurong West, Singapore

3. Tetras.AI, Hong Kong, China

Funder

RIE2020 Industry Alignment Fund – Industry Collaboration Projects (IAF-ICP) Funding Initiative, as well as cash and in-kind contribution from the industry partne

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Cited by 7 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Quality and recognizability estimation video encryption database;Information Sciences;2024-09

2. Deep Hybrid Camera Deblurring for Smartphone Cameras;Special Interest Group on Computer Graphics and Interactive Techniques Conference Conference Papers '24;2024-07-13

3. PAPS-OVQA: Projection-Aware Patch Sampling for Omnidirectional Video Quality Assessment;2024 IEEE International Symposium on Circuits and Systems (ISCAS);2024-05-19

4. Review of Image Quality Assessment Methods for Compressed Images;Journal of Imaging;2024-05-08

5. Multi-dataset learning with channel modulation loss for blind image quality assessment;Multimedia Tools and Applications;2024-04-01

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