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Models trained with VBVR-Pro not only excel in a controlled task space but also show significant transferability to external benchmarks, revealing critical insights into visual reasoning mechanisms.
ACE-Data-0 reveals that existing models struggle significantly with complex interactions, exposing critical gaps in embodied AI performance.
A single framework now generates simulation-ready 3D assets for rigid, deformable, and articulated objects, unlocking new possibilities for embodied AI and physics-based simulation.
Finally, a method exists to create 3D human-scene interaction models from casual captures that are stable enough for use in physics simulations and deployment on real-world robots.
Unlock real-world embodied AI: EmbodMocap's affordable dual-iPhone setup captures scene-aware human motion data, enabling robots to learn from human actions in everyday environments.
