mlsanityData to 7 Oct 2026

AJAHR: Amputated Joint Aware 3D Human Mesh Recovery

arXiv 2509.19939 ↗First posted 24 Sep 2025cs.GR cs.AI cs.CVcited by 3

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Abstract (arXiv)

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 the project webpage.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 37 of its 57 references that are in the map. First posted on arXiv 24 Sep 2025.

Builds on

37 of 57 references.

References · 37

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25 more
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 3.

3 papers.