한국정보처리학회:학술대회논문집 (Proceedings of the Korea Information Processing Society Conference)

한국정보처리학회 (Korea Information Processing Society)
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RGB 이미지에서 트랜스포머 기반 고밀도 3D 재구성

Transformer-based dense 3D reconstruction from RGB images

  • 서가가 (동국대학교 멀티미디어공학과) ;
  • 고서 (동국대학교 멀티미디어공학과) ;
  • 문명운 (동국대학교 멀티미디어공학과) ;
  • 조경은 (동국대학교 멀티미디어공학과)
  • Xu, Jiajia (Department of Multimedia Engineering, Dongguk University-Seoul) ;
  • Gao, Rui (Department of Multimedia Engineering, Dongguk University-Seoul) ;
  • Wen, Mingyun (Department of Multimedia Engineering, Dongguk University-Seoul) ;
  • Cho, Kyungeun (Department of Multimedia Engineering, Dongguk University-Seoul)
  • 발행 : 2022.11.21
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초록

Multiview stereo (MVS) 3D reconstruction of a scene from images is a fundamental computer vision problem that has been thoroughly researched in recent times. Traditionally, MVS approaches create dense correspondences by constructing regularizations and hand-crafted similarity metrics. Although these techniques have achieved excellent results in the best Lambertian conditions, traditional MVS algorithms still contain a lot of artifacts. Therefore, in this study, we suggest using a transformer network to accelerate the MVS reconstruction. The network is based on a transformer model and can extract dense features with 3D consistency and global context, which are necessary to provide accurate matching for MVS.

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과제정보

This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIT) (No. 2022R1A2C200686411).