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Identity-Aware Fusion for Interactive Human Mesh Reconstruction
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- Authors
- Sungmin Jang, Wonjun Kim
- Issue Date
- 2026-03
- Citation
- IEEE Signal Processing Letters, v.33, pp.1215-1219
- ISSN
- 1070-9908
- Publisher
- IEEE
- Language
- English
- Type
- Journal Article
- Abstract
- Even though recent studies have demonstrated significant improvements in 3D human mesh reconstruction, most methods still face challenges under occlusions. To mitigate this issue, multi-view human mesh reconstruction methods have been proposed, which leverage additional visual cues by aggregating the complementary information. However, in scenes with close human interactions, the identity of each person is hard to be preserved across different views, thus leading to incorrect merging of visual features between individuals. To address this limitation, we propose an identity-aware fusion scheme for interactive human mesh reconstruction. The key idea is to maintain the identity of each person across different views based on the shape feature from the anchor view, which is determined by the highest visibility of each person. This helps the model to distinguish features encoded from each person during the aggregation process, even under close interactions with severe occlusions, leading to the reliable reconstruction of 3D human meshes. Furthermore, we design a weighting scheme to adaptively fuse joints belonging to the same identity across different views while allowing the model to focus more on visible joints. Experimental results on benchmark datasets show that the proposed method efficiently improves the performance of interactive human mesh reconstruction.
- Keyword
- 3D human mesh reconstruction, close human interaction, multi-view methods
- KSP Keywords
- Aggregation process, Benchmark datasets, Human interaction, Mesh reconstruction, Multi-view, Reconstruction method, Visual Features, Visual cues, Weighting Scheme, fusion scheme, shape feature