GAS (Grasp Area Segmentation) dataset consists of 10089 RGB images of cluttered scenes grouped into 1121 grasp-area segmentation tasks. For each RGB image we provide a binary segmentation map with the graspable and non-graspable regions for every object in the scene. For creating the GAS dataset we use the RGB images and corresponding ground truth segmentation masks from the GraspNet 1-Billion dataset.
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