ETH Zurich's EgoPHI estimates 3D hand-object contact and force from one egocentric image
cholz · x · 2026-09-10
Christian Holz's group at ETH Zurich presents EgoPHI (ECCV 2026), the first vision-based model to jointly estimate dense contact maps and 3D force distributions on hand and articulated object meshes from a single egocentric RGB image plus object geometry.
- Approach: registers hand meshes to iteratively refine object pose under occlusion, fuses image features with 3D geometry, and uses graph attention plus cross-attention to model intra-mesh geometry and hand-object relations, predicting per-vertex contact and 3D force direction.
- Data: a physics-simulation pipeline augments ARCTIC and H2O with dense per-vertex contact+force supervision, addressing the lack of scalable force ground truth; tests cover in-distribution and out-of-distribution benchmarks.
- Sim2real: instrumented cube and cylinder objects captured dense contact and force data from eight participants to evaluate transfer.
- Paper, code, and dataset are released.
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