Occlusion-Aware Manga Character Re-identification with Self-Paced Contrastive Learning

Ci Yin Zhang, Wei Ta Chu

研究成果: Conference contribution

摘要

Existing methods for manga character re-identification primarily rely on facial information, overlooking the unique characteristics of characters’ bodies and failing to address common challenges like occlusion by speech balloons and incomplete body parts. To tackle these issues, we propose a method called Occlusion-Aware Manga Character Re-identification (OAM-ReID) with self-paced contrastive learning, which leverages annotated body data from the Manga109 dataset for training. By synthesizing data with occluded speech balloons and incomplete bodies, we empower the framework to be aware of occlusion, so that more effective feature representations are learnt. Experimental results show that this approach outperforms the state-of-the-art person ReID method.

原文English
主出版物標題Proceedings of the 5th ACM International Conference on Multimedia in Asia, MMAsia 2023
發行者Association for Computing Machinery, Inc
ISBN(電子)9798400702051
DOIs
出版狀態Published - 2023 12月 6
事件5th ACM International Conference on Multimedia in Asia, MMAsia 2023 - Hybrid, Tainan, Taiwan
持續時間: 2023 12月 62023 12月 8

出版系列

名字Proceedings of the 5th ACM International Conference on Multimedia in Asia, MMAsia 2023

Conference

Conference5th ACM International Conference on Multimedia in Asia, MMAsia 2023
國家/地區Taiwan
城市Hybrid, Tainan
期間23-12-0623-12-08

All Science Journal Classification (ASJC) codes

  • 電腦繪圖與電腦輔助設計
  • 人機介面

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