Joint Reconstruction of 3D Human and Object via Contact-Based Refinement
  Transformer
Hyeongjin Nam Daniel Sungho Jung Gyeongsik Moon Kyoung Mu Lee
Human-object contact serves as a strong cue to understand how humans
physically interact with objects. Nevertheless, it is not widely explored to
utilize human-object contact information for the joint reconstruction of 3D
human and object from a single image. In this work, we present a novel joint 3D
human-object reconstruction method (CONTHO) that effectively exploits contact
information between humans and objects. There are two core designs in our
system: 1) 3D-guided contact estimation and 2) contact-based 3D human and
object refinement. First, for accurate human-object contact estimation, CONTHO
initially reconstructs 3D humans and objects and utilizes them as explicit 3D
guidance for contact estimation. Second, to refine the initial reconstructions
of 3D human and object, we propose a novel contact-based refinement Transformer
that effectively aggregates human features and object features based on the
estimated human-object contact. The proposed contact-based refinement prevents
the learning of erroneous correlation between human and object, which enables
accurate 3D reconstruction. As a result, our CONTHO achieves state-of-the-art
performance in both human-object contact estimation and joint reconstruction of
3D human and object. The code is publicly available at
https://github.com/dqj5182/CONTHO_RELEASE.