Single-image coherent reconstruction of objects and humans
- URL: http://arxiv.org/abs/2408.08086v1
- Date: Thu, 15 Aug 2024 11:27:18 GMT
- Title: Single-image coherent reconstruction of objects and humans
- Authors: Sarthak Batra, Partha P. Chakrabarti, Simon Hadfield, Armin Mustafa,
- Abstract summary: Existing methods for reconstructing objects and humans from a monocular image suffer from severe mesh collisions and performance limitations.
This paper introduces a method to obtain a globally consistent 3D reconstruction of interacting objects and people from a single image.
- Score: 16.836684199314938
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Existing methods for reconstructing objects and humans from a monocular image suffer from severe mesh collisions and performance limitations for interacting occluding objects. This paper introduces a method to obtain a globally consistent 3D reconstruction of interacting objects and people from a single image. Our contributions include: 1) an optimization framework, featuring a collision loss, tailored to handle human-object and human-human interactions, ensuring spatially coherent scene reconstruction; and 2) a novel technique to robustly estimate 6 degrees of freedom (DOF) poses, specifically for heavily occluded objects, exploiting image inpainting. Notably, our proposed method operates effectively on images from real-world scenarios, without necessitating scene or object-level 3D supervision. Extensive qualitative and quantitative evaluation against existing methods demonstrates a significant reduction in collisions in the final reconstructions of scenes with multiple interacting humans and objects and a more coherent scene reconstruction.
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