Abstract: We propose a co-part segmentation method that takes a set of point clouds of the same category as input where neither a ground truth label nor a prior network is required. With difficulties ...
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Abstract: Existing methods for learning 3D point cloud representation often use a single dataset-specific training and testing approach, leading to performance drops due to significant domain shifts ...
Abstract: The point cloud feature aggregation, which learns discriminative features from the disordered points, plays a key role for large-scale point cloud semantic segmentation. Most previous ...