Temporally Consistent Amodal Completion for 3D Human-Object Interaction Reconstruction
Journal:
arXiv
Published Date:
Jul 10, 2025
Abstract
We introduce a novel framework for reconstructing dynamic human-object
interactions from monocular video that overcomes challenges associated with
occlusions and temporal inconsistencies. Traditional 3D reconstruction methods
typically assume static objects or full visibility of dynamic subjects, leading
to degraded performance when these assumptions are violated-particularly in
scenarios where mutual occlusions occur. To address this, our framework
leverages amodal completion to infer the complete structure of partially
obscured regions. Unlike conventional approaches that operate on individual
frames, our method integrates temporal context, enforcing coherence across
video sequences to incrementally refine and stabilize reconstructions. This
template-free strategy adapts to varying conditions without relying on
predefined models, significantly enhancing the recovery of intricate details in
dynamic scenes. We validate our approach using 3D Gaussian Splatting on
challenging monocular videos, demonstrating superior precision in handling
occlusions and maintaining temporal stability compared to existing techniques.
