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Language-Level Semantics Conditioned 3D Point Cloud Segmentation
[article]
2022
arXiv
pre-print
In this work, a language-level Semantics Conditioned framework for 3D Point cloud segmentation, called SeCondPoint, is proposed, where language-level semantics are introduced to condition the modeling of point feature distribution as well as the pseudo-feature generation, and a feature-geometry-based mixup approach is further proposed to facilitate the distribution learning. To our knowledge, this is the first attempt in literature to introduce language-level semantics to the 3D point cloud
arXiv:2107.00430v3
fatcat:p536hu7levbe3o63dj5adku2me