AesCLIP: Multi-Attribute Contrastive Learning for Image Aesthetics Assessment-Reference-Cited by-同舟云学术

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AesCLIP: Multi-Attribute Contrastive Learning for Image Aesthetics Assessment

Published:2023-10-26 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 31st ACM International Conference on Multimedia
language:
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Author:

Sheng Xiangfei¹^ORCID,Li Leida¹^ORCID,Chen Pengfei¹^ORCID,Wu Jinjian¹^ORCID,Dong Weisheng¹^ORCID,Yang Yuzhe²^ORCID,Xu Liwu²^ORCID,Li Yaqian²^ORCID,Shi Guangming¹^ORCID

Affiliation:

1. Xidian University, Xi'an, China

2. OPPO Research Institute, Shanghai, China

Funder

National Natural Science Foundation of China

OPPO Research Fund

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3581783.3611969

Reference54 articles.

1. Steven Bird , Ewan Klein , and Edward Loper . 2009. Natural Language Processing with Python: Analyzing Text with the Natural Language Toolkit. "O'Reilly Media , Inc .". Steven Bird, Ewan Klein, and Edward Loper. 2009. Natural Language Processing with Python: Analyzing Text with the Natural Language Toolkit. "O'Reilly Media, Inc.".

2. Composition and Style Attributes Guided Image Aesthetic Assessment

3. Kuang-Yu Chang , Kung-Hung Lu , and Chu-Song Chen . 2017 . Aesthetic Critiques Generation for Photos . In Proceedings of the IEEE International Conference on Computer Vision. IEEE, 3534--3543 . Kuang-Yu Chang, Kung-Hung Lu, and Chu-Song Chen. 2017. Aesthetic Critiques Generation for Photos. In Proceedings of the IEEE International Conference on Computer Vision. IEEE, 3534--3543.

4. Distilling Audio-Visual Knowledge by Compositional Contrastive Learning

5. Image Aesthetic Assessment: An experimental survey

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