Attention-based Multi-Patch Aggregation for Image Aesthetic Assessment-Reference-Cited by-同舟云学术

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Attention-based Multi-Patch Aggregation for Image Aesthetic Assessment

Published:2018-10-15 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 26th ACM international conference on Multimedia
language:
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Author:

Sheng Kekai¹,Dong Weiming²,Ma Chongyang³,Mei Xing³,Huang Feiyue⁴,Hu Bao-Gang²

Affiliation:

1. NLPR, Institute of Automation, Chinese Academy of Sciences & University of Chinese Academy of Sciences, Beijing, China

2. NLPR, Institute of Automation, Chinese Academy of Sciences, Beijing, China

3. Snap Inc., Los Angeles, CA, USA

4. Tencent, Shanghai, China

Funder

National Natural Science Foundation of China

Beijing Natural Science Foundation

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3240508.3240554

Reference36 articles.

1. A holistic approach to aesthetic enhancement of photographs

2. Look and Think Twice: Capturing Top-Down Visual Attention with Feedback Convolutional Neural Networks

3. Learning to Compose with Professional Photographs on the Web

4. Studying Aesthetics in Photographic Images Using a Computational Approach

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1. Improving Image Aesthetic Assessment via Multiple Image Joint Learning;ACM Transactions on Multimedia Computing, Communications, and Applications;2024-08-21

2. Semantic and style based multiple reference learning for artistic and general image aesthetic assessment;Neurocomputing;2024-05

3. Towards Data-Driving Multi-View Evaluation Framework for Scratch;Tsinghua Science and Technology;2024-04

4. A Mobile Image Aesthetics Processing System with Intelligent Scene Perception;Applied Sciences;2024-01-18

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