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3D Point Cloud Data and Processing
3D point cloud data can be obtained by laser scanning or photogrammetry and can also be seen as a representation of 3D digitization of the physical...
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Point-voxel dual stream transformer for 3d point cloud learning
Recently, the success of Transformer in natural language processing and image processing inspires researchers to apply Transformer in point cloud...
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Learning Key Features Transformer Network for Point Cloud Processing
Due to the unordered and irregular nature of point cloud data, it is challenging for neural networks to learn from it. Attention mechanisms have...
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Improved grid refine segmentation for 3D point cloud in video-based point cloud compression (V-PCC)
For an immersive visual communication experience, it is essential to enable technologies that can capture and transmit point clouds capable of...
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PointSGLN: a novel point cloud classification network based on sampling grou** and local point normalization
The point cloud data structure is characterized by disorder and spatial irregularity, which makes it impossible to apply 2D convolutional neural...
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A comprehensive overview of deep learning techniques for 3D point cloud classification and semantic segmentation
Point cloud analysis has a wide range of applications in many areas such as computer vision, robotic manipulation, and autonomous driving. While deep...
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Conversion of Point Cloud Data to 3D Models Using PointNet++ and Transformer
AbstractThis paper presents an approach to 3D model reconstruction from point cloud data using modern neural network architectures. The method is...
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Noise4Denoise: Leveraging noise for unsupervised point cloud denoising
Existing deep learning-based point cloud denoising methods are generally trained in a supervised manner that requires clean data as ground-truth...
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A review of point cloud segmentation for understanding 3D indoor scenes
Point cloud segmentation is an essential task in three-dimensional (3D) vision and intelligence. It is a critical step in understanding 3D scenes...
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Latent diffusion transformer for point cloud generation
Diffusion models have been successfully applied to point cloud generation tasks recently. The main notion is using a forward process to progressively...
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Edge-guided generative network with attention for point cloud completion
Point clouds acquired through 3D scanning devices often suffer from sparsity and incompleteness due to reflection, device resolution, and viewing...
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Retrieval-and-alignment based large-scale indoor point cloud semantic segmentation
Current methods for point cloud semantic segmentation depend on the extraction of descriptive features. However, unlike images, point clouds are...
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Two-view point cloud registration network: feature and geometry
Rigid point cloud registration is a crucial upstream task in computer vision, whose goal is to align two misaligned point clouds using a rigid...
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TopologyFormer: structure transformer assisted topology reconstruction for point cloud completion
Point cloud completion is a fundamental task to enhance the completeness and authenticity of point cloud data captured in the real world. Existing...
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Training-Free NAS for 3D Point Cloud Processing
Deep neural networks for 3D point cloud processing have exhibited superior performance on many tasks. However, the structure and computational...
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Towards uniform point distribution in feature-preserving point cloud filtering
While a popular representation of 3D data, point clouds may contain noise and need filtering before use. Existing point cloud filtering methods...
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Self-supervised indoor scene point cloud completion from a single panorama
In this paper, we propose a self-supervised learning method of point cloud completion for indoor scenes. Considering the limited view of single-view...
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Redundant same sequence point cloud registration
Many point cloud registration methods rely on establishing correspondence pairs in order to solve the registration problem. However, their...
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Online static point cloud map construction based on 3D point clouds and 2D images
With the development of science and technology, robots have been applied to many fields to free people’s hands. Environment perception and map...
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Learning Temporal Variations for 4D Point Cloud Segmentation
LiDAR-based 3D scene perception is a fundamental and important task for autonomous driving. Most state-of-the-art methods on LiDAR-based 3D...
