ArtHOI: Articulated Human-Object Interaction Synthesis by 4D Reconstruction From Video Priors

Synthesizing physically plausible articulated human-object interactions (HOI) without 3D/4D supervision remains a fundamental challenge. Recent zero-shot approaches use generative priors for 4D human-object interaction synthesis, but recovering explicit articulated object geometry from monocular video remains challenging. We formulate articulated HOI synthesis as a 4D reconstruction problem from monocular video priors. Given a video generated by a diffusion model and initial 3D assets, we reconstruct a full 4D articulated scene without 3D motion supervision. This reconstruction-based approach treats the generated 2D video as supervision for an inverse rendering problem, recovering geometrically consistent and physically plausible 4D scenes that naturally respect contact, articulation, and temporal coherence. We introduce ArtHOI, a zero-shot system that integrates two stages for articulated human-object interaction synthesis. 1) Flow-based part segmentation maps optical-flow cues and SAM masks to 3D Gaussian parts, using quasi-static binding to separate moving and static regions. 2) Decoupled reconstruction first recovers articulated object geometry and then refines human motion using contact targets derived from the fixed object reconstruction. ArtHOI bridges video-based generation and geometry-aware reconstruction, producing interactions that are both semantically aligned and physically grounded. Across diverse articulated scenes (e.g., opening fridges, cabinets, microwaves), ArtHOI reconstructs explicit part articulation and uses the reconstructed geometry to guide human motion refinement. The project page is available at https://arthoi.github.io/.