AJAHR: Amputated Joint Aware 3D Human Mesh Recovery

Citations

SCOPUS

3

초록

Existing human mesh recovery methods assume a standard human body structure, overlooking diverse anatomical conditions such as limb loss. This assumption introduces bias when applied to individuals with amputations-a limitation further exacerbated by the scarcity of suitable datasets. To address this gap, we propose Amputated Joint Aware 3D Human Mesh Recovery (AJAHR), which is an adaptive pose estimation framework that improves mesh reconstruction for individuals with limb loss. Our model integrates a body-part amputation classifier, jointly trained with the mesh recovery network, to detect potential amputations. We also introduce Amputee 3D (A3D), which is a synthetic dataset offering a wide range of amputee poses for robust training. While maintaining competitive performance on non-amputees, our approach achieves state-of-the-art results for amputated individuals. Additional materials can be found at: https://chojinie.github.io/project_AJAHR/

키워드

human mesh recovery; human pose and shape estimation; inclusive human behavior model
제목
AJAHR: Amputated Joint Aware 3D Human Mesh Recovery
저자
Cho, Hyunjin; Choi, Giyun; Choi, Jongwon
DOI
10.1109/ICCV51701.2025.00743
발행일
2025
유형
Conference Paper
저널명
Proceedings of the IEEE International Conference on Computer Vision
페이지
7925 ~ 7935