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Exploring quality camouflage for social images

科研成果: 期刊稿件会议文章同行评审

摘要

Social images can be misused in ways not anticipated or intended by the people who share them online. In particular, high-quality images can be driven to unwanted prominence by search engines or used to train unscrupulous AI. The risk of misuse can be reduced if photos can evade quality filtering, which is commonly carried out by automatic Blind Image Quality Assessment (BIQA) algorithms. The Pixel Privacy Task benchmarks privacy-protective approaches that shield images against unethical computer vision algorithms. In the 2020 task, participants are asked to develop quality camouflage methods that can effectively decrease the BIQA score of high-quality images while maintaining image appeal. The camouflage should not damage the image from the point of view of the user: it needs to be either imperceptible, or else to enhance the image visibly, to the human eye.

源语言英语
期刊CEUR Workshop Proceedings
2882
出版状态已出版 - 2020
已对外发布
活动Multimedia Evaluation Benchmark Workshop 2020, MediaEval 2020 - Virtual, Online
期限: 14 12月 202015 12月 2020

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