SID achieves approximately 90% success on six real-world manipulation tasks with only two demonstrations under out-of-distribution initializations, with less than 10% performance drop under distractors and disturbances.
kpam: Keypoint affordances for category-level robotic manipulation
3 Pith papers cite this work. Polarity classification is still indexing.
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Part decomposition with generative shape models allows one-shot robot skill transfer across unfamiliar object geometries in simulation and real settings.
AFFORD2ACT distills a minimal set of affordance-guided 2D keypoints from text and a single image to train a 38-dimensional gated transformer policy that achieves 82% success on unseen objects and scenes.
citing papers explorer
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SID: Sliding into Distribution for Robust Few-Demonstration Manipulation
SID achieves approximately 90% success on six real-world manipulation tasks with only two demonstrations under out-of-distribution initializations, with less than 10% performance drop under distractors and disturbances.
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One-Shot Cross-Geometry Skill Transfer through Part Decomposition
Part decomposition with generative shape models allows one-shot robot skill transfer across unfamiliar object geometries in simulation and real settings.
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AFFORD2ACT: Affordance-Guided Automatic Keypoint Selection for Generalizable and Lightweight Robotic Manipulation
AFFORD2ACT distills a minimal set of affordance-guided 2D keypoints from text and a single image to train a 38-dimensional gated transformer policy that achieves 82% success on unseen objects and scenes.