Primitive-Based 3D Human-Object Interaction Modelling and Programming

Authors

  • Siqi Liu Shanghai Jiao Tong University
  • Yong-Lu Li Shanghai Jiao Tong University
  • Zhou Fang Shanghai Jiaotong University
  • Xinpeng Liu Shanghai Jiao Tong University
  • Yang You Shanghai Jiao Tong University
  • Cewu Lu Shanghai Jiao Tong University

DOI:

https://doi.org/10.1609/aaai.v38i4.28161

Keywords:

CV: 3D Computer Vision, CV: Representation Learning for Vision

Abstract

Embedding Human and Articulated Object Interaction (HAOI) in 3D is an important direction for a deeper human activity understanding. Different from previous works that use parametric and CAD models to represent humans and objects, in this work, we propose a novel 3D geometric primitive-based language to encode both humans and objects. Given our new paradigm, humans and objects are all compositions of primitives instead of heterogeneous entities. Thus, mutual information learning may be achieved between the limited 3D data of humans and different object categories. Moreover, considering the simplicity of the expression and the richness of the information it contains, we choose the superquadric as the primitive representation. To explore an effective embedding of HAOI for the machine, we build a new benchmark on 3D HAOI consisting of primitives together with their images and propose a task requiring machines to recover 3D HAOI using primitives from images. Moreover, we propose a baseline of single-view 3D reconstruction on HAOI. We believe this primitive-based 3D HAOI representation would pave the way for 3D HAOI studies. Our code and data are available at https://mvig-rhos.com/p3haoi.

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Published

2024-03-24

How to Cite

Liu, S., Li, Y.-L., Fang, Z., Liu, X., You, Y., & Lu, C. (2024). Primitive-Based 3D Human-Object Interaction Modelling and Programming. Proceedings of the AAAI Conference on Artificial Intelligence, 38(4), 3711-3719. https://doi.org/10.1609/aaai.v38i4.28161

Issue

Section

AAAI Technical Track on Computer Vision III