A two-stage language-driven grasping system that pools visual features inside a predicted object mask improves grasp accuracy and training efficiency versus CLIP baselines, supported by a new 219M-grasp dataset.
Jacquard: A large scale dataset for robotic grasp detection
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MapleGrasp: Mask-guided Feature Pooling for Language-driven Efficient Robotic Grasping
A two-stage language-driven grasping system that pools visual features inside a predicted object mask improves grasp accuracy and training efficiency versus CLIP baselines, supported by a new 219M-grasp dataset.