A bidirectional vision-language-depth fusion model, OGRG, outperforms prior baselines in grounding and grasping objects described by spatial language, including with duplicate objects and weak grasp labels.
Antipodal robotic grasping using generative residual convolutional neural network,
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Attribute-based Object Grounding and Robot Grasp Detection with Spatial Reasoning
A bidirectional vision-language-depth fusion model, OGRG, outperforms prior baselines in grounding and grasping objects described by spatial language, including with duplicate objects and weak grasp labels.