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SPU-Net: Self-Supervised Point Cloud Upsampling by Coarse-to-Fine Reconstruction With Self-Projection Optimization.

, , , and . IEEE Trans. Image Process., (2022)

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Parts4Feature: Learning 3D Global Features from Generally Semantic Parts in Multiple Views., , , and . IJCAI, page 766-773. ijcai.org, (2019)LRC-Net: Learning discriminative features on point clouds by encoding local region contexts., , , , and . Comput. Aided Geom. Des., (2020)Application of Image SIFT Features to the Context of CBIR., , , , and . CSSE (4), page 552-555. IEEE Computer Society, (2008)978-0-7695-3336-0.Fine-Grained 3D Shape Classification with Hierarchical Part-View Attentions., , , and . CoRR, (2020)Point2SpatialCapsule: Aggregating Features and Spatial Relationships of Local Regions on Point Clouds using Spatial-aware Capsules., , , and . CoRR, (2019)SPU-Net: Self-Supervised Point Cloud Upsampling by Coarse-to-Fine Reconstruction with Self-Projection Optimization., , , and . CoRR, (2020)D-Net: Learning for Distinctive Point Clouds by Self-Attentive Point Searching and Learnable Feature Fusion., , , , and . CoRR, (2023)Point2SpatialCapsule: Aggregating Features and Spatial Relationships of Local Regions on Point Clouds Using Spatial-Aware Capsules., , , and . IEEE Trans. Image Process., (2020)Fine-Grained 3D Shape Classification With Hierarchical Part-View Attention., , , and . IEEE Trans. Image Process., (2021)Point2Sequence: Learning the Shape Representation of 3D Point Clouds with an Attention-Based Sequence to Sequence Network., , , and . AAAI, page 8778-8785. AAAI Press, (2019)