Pxform dataset and PartFlow network enable feedforward 3D editing by learning from semantic-part transformations and achieve SOTA on geometric and appearance benchmarks.
P3-sam: Native 3d part segmentation
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S2AM3D combines multi-view 2D priors with 3D contrastive learning and a scale-aware decoder to deliver consistent, granularity-controllable part segmentation on point clouds, supported by a new dataset exceeding 100k samples.
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Feedforward 3D Editing Learns from Semantic-Part Transformation
Pxform dataset and PartFlow network enable feedforward 3D editing by learning from semantic-part transformations and achieve SOTA on geometric and appearance benchmarks.
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S2AM3D: Scale-controllable Part Segmentation of 3D Point Clouds
S2AM3D combines multi-view 2D priors with 3D contrastive learning and a scale-aware decoder to deliver consistent, granularity-controllable part segmentation on point clouds, supported by a new dataset exceeding 100k samples.