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3D Map Reconstruction From Single Satellite Image Using a Deep Monocular Depth Network
- Son, Changmin;
- Park, Soon-Yong
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6초록
In this paper, we propose a 3D reconstruction scheme from single image with deep monocular depth estimation network, BTS (From Big to Small: Multi-Scale Local Planar Guidance for Monocular Depth Estimation) [1]. Furthermore, we expand it to height estimation focused building from remote sensing images. To address these issues, we substitute depth estimation loss function with height estimation loss function. Moreover, considering improving the quality of the building height map and looking as similar as possible to the ground-truth view, we apply building adaptive loss function.
키워드
3D map; Monocular height estimation; Deep learning; Remote sensing image
- 제목
- 3D Map Reconstruction From Single Satellite Image Using a Deep Monocular Depth Network
- 저자
- Son, Changmin; Park, Soon-Yong
- 발행일
- 2022
- 유형
- Proceedings Paper
- 저널명
- 2022 THIRTEENTH INTERNATIONAL CONFERENCE ON UBIQUITOUS AND FUTURE NETWORKS (ICUFN)
- 페이지
- 5 ~ 7
- 언어
- ENG
- 출판사
- IEEE
- 발행국가
- 미국
- 분량
- 3 페이지
- ISSN
- E 2165-8536
P 2165-8528