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RoboDojo reveals that existing benchmarks fail to capture the full spectrum of robot manipulation capabilities, paving the way for more robust evaluations that bridge the gap between simulation and real-world performance.
IV-CoT reveals that separating structural planning from appearance rendering can dramatically enhance the fidelity of text-to-image generation.
Generating realistic human interactions with objects and scenes is now possible even with limited data, thanks to a clever training strategy that combines synthetic and real data.
Forget painstakingly creating 3D assets for robot training - ManiTwin automates the process, turning single images into simulation-ready objects at scale.
