EgoAERO reconstructs contact-consistent hand-object trajectories from single egocentric RGB-D videos without object assets via asset-free tracking and adaptive optimization, then trains robot policies with two-stage residual learning, achieving performance close to CAD-based methods.
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2026 2verdicts
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Introduces a terrain-specific benchmark showing cross-domain gaps in INR methods and demonstrates that HUVR+SIREN achieves superior height and derivative fidelity in a compact quantized format.
citing papers explorer
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EgoAERO: Learning Dexterous Manipulation from a Single Egocentric Video without Object Assets
EgoAERO reconstructs contact-consistent hand-object trajectories from single egocentric RGB-D videos without object assets via asset-free tracking and adaptive optimization, then trains robot policies with two-stage residual learning, achieving performance close to CAD-based methods.
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Rethinking Amortized Neural Representations for High-Resolution Terrain Elevation Data
Introduces a terrain-specific benchmark showing cross-domain gaps in INR methods and demonstrates that HUVR+SIREN achieves superior height and derivative fidelity in a compact quantized format.