GraphiContact: Pose-aware Human-Scene Robust Contact Perception for Interactive Systems

TL;DR

GraphiContact is a pose-aware framework that jointly predicts vertex-level human-scene contact and 3D human mesh reconstruction from a single image, improving robustness under occlusion and noise for interactive systems.

Contribution

It introduces a novel pose-aware method with dual Transformer encoders and a training strategy that enhances contact prediction robustness in real-world scenarios.

Findings

Achieves consistent improvements on contact prediction and 3D reconstruction benchmarks.

Effectively handles occlusion and perceptual noise during contact inference.

Provides a comprehensive tool for human interaction analysis.

Abstract

Monocular vertex-level human-scene contact prediction is a fundamental capability for interactive systems such as assistive monitoring, embodied AI, and rehabilitation analysis. In this work, we study this task jointly with single-image 3D human mesh reconstruction, using reconstructed body geometry as a scaffold for contact reasoning. Existing approaches either focus on contact prediction without sufficiently exploiting explicit 3D human priors, or emphasize pose/mesh reconstruction without directly optimizing robust vertex-level contact inference under occlusion and perceptual noise. To address this gap, we propose GraphiContact, a pose-aware framework that transfers complementary human priors from two pretrained Transformer encoders and predicts per-vertex human-scene contact on the reconstructed mesh. To improve robustness in real-world scenarios, we further introduce a Single-Image Multi-Infer Uncertainty (SIMU) training strategy with token-level adaptive routing, which simulates occlusion and noisy observations during training while preserving efficient single-branch inference at test time. Experiments on five benchmark datasets show that GraphiContact achieves consistent gains on both contact prediction and 3D human reconstruction. Our code, based on the GraphiContact method, provides comprehensive 3D human reconstruction and interaction analysis, and will be publicly available at https://github.com/Aveiro-Lin/GraphiContact.