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Forget explicit labels: this method learns object co-occurrence priors directly from unlabeled visual data, rivaling human search efficiency.
Robots can now build 3D scene graphs that understand how objects move, enabling more robust manipulation of articulated objects in real-world environments.
Skip directly learning actions and instead infer the "what" of robotic manipulation tasks by extracting sparse graphical task models from just a few demonstrations.
