Local-non-local complementary learning network for 3D point cloud analysis
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DOI: 10.1038/s41598-024-84248-9
Abstract: Point cloud analysis is integral to numerous applications, including mapping and autonomous driving. However, the unstructured and disordered nature of point clouds presents significant challenges for feature extraction. While both local and non-local features are… read more here.
Keywords: local non; cloud analysis; non local; point cloud ... See more keywords
Geometrically aware transformer for point cloud analysis
Sign Up to like & getrecommendations! Published in 2025 at "Scientific Reports"
DOI: 10.1038/s41598-025-00789-7
Abstract: With the increasing use of 3D point cloud data in autonomous driving, robotic perception, and remote sensing, efficient and accurate point cloud analysis remains a critical challenge. This study presents PointGA, a lightweight Transformer-based model… read more here.
Keywords: cloud analysis; point; geometrically aware; point cloud ... See more keywords
Learning Discriminative Features by Covering Local Geometric Space for Point Cloud Analysis
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2022.3170493
Abstract: At present, effectively aggregating and transferring the local features of point cloud is still an unresolved technological conundrum. In this study, we propose a new space-cover convolutional neural network (SC-CNN) for tasks such as point… read more here.
Keywords: point cloud; space; geometry; cloud analysis ... See more keywords
PointMT: Efficient Point Cloud Analysis With Hybrid MLP-Transformer Architecture
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Transactions on Multimedia"
DOI: 10.1109/tmm.2025.3581747
Abstract: In recent years, point cloud analysis methods based on the Transformer architecture have made significant progress, particularly in the context of multimedia applications such as 3D modeling, virtual reality, and autonomous systems. However, the Transformer… read more here.
Keywords: architecture; point; cloud analysis; point cloud ... See more keywords
A Rotation-Invariant Framework for Deep Point Cloud Analysis
Sign Up to like & getrecommendations! Published in 2021 at "IEEE transactions on visualization and computer graphics"
DOI: 10.1109/tvcg.2021.3092570
Abstract: Recently, many deep neural networks were designed to process 3D point clouds, but a common drawback is that rotation invariance is not ensured, leading to poor generalization to arbitrary orientations. In this paper, we introduce… read more here.
Keywords: cloud analysis; point cloud; rotation; rotation invariant ... See more keywords