Statistics for topic point-cloud
RepositoryStats tracks 615,808 Github repositories, of these 436 are tagged with the point-cloud topic. The most common primary language for repositories using this topic is Python (259). Other languages include: C++ (96), Jupyter Notebook (11)
Stargazers over time for topic point-cloud
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3DGS-to-PC: Convert a 3D gaussian splatting scene into a dense point cloud or basic mesh with advanced customisation options and high-accuracy rendered point colours
PointNet and PointNet++ implemented by pytorch (pure python) and on ModelNet, ShapeNet and S3DIS.
Pointcept: a codebase for point cloud perception research. Latest works: PTv3 (CVPR'24 Oral), PPT (CVPR'24), OA-CNNs (CVPR'24), MSC (CVPR'23)
3DGS-to-PC: Convert a 3D gaussian splatting scene into a dense point cloud or basic mesh with advanced customisation options and high-accuracy rendered point colours
MapEval: Towards Unified, Robust and Efficient SLAM Map Evaluation Framework.
Reconstructing compact building models from point clouds using deep implicit fields [ISPRS 2022]
Official PyTorch implementation of Superpoint Transformer introduced in [ICCV'23] "Efficient 3D Semantic Segmentation with Superpoint Transformer" and SuperCluster introduced in [3DV'24 Oral] "Scalabl...
PointNet and PointNet++ implemented by pytorch (pure python) and on ModelNet, ShapeNet and S3DIS.
OpenMMLab's next-generation platform for general 3D object detection.
Pointcept: a codebase for point cloud perception research. Latest works: PTv3 (CVPR'24 Oral), PPT (CVPR'24), OA-CNNs (CVPR'24), MSC (CVPR'23)
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
Convert various AEC model formats for efficient viewing in the browser with xeokit.
3DGS-to-PC: Convert a 3D gaussian splatting scene into a dense point cloud or basic mesh with advanced customisation options and high-accuracy rendered point colours
MapEval: Towards Unified, Robust and Efficient SLAM Map Evaluation Framework.
Python efficient farthest point sampling (FPS) library. Compatible with numpy.
3DGS-to-PC: Convert a 3D gaussian splatting scene into a dense point cloud or basic mesh with advanced customisation options and high-accuracy rendered point colours
OpenMMLab's next-generation platform for general 3D object detection.
User-friendly, commercial-grade software for processing aerial imagery. 🛩
PointNet and PointNet++ implemented by pytorch (pure python) and on ModelNet, ShapeNet and S3DIS.
3DGS-to-PC: Convert a 3D gaussian splatting scene into a dense point cloud or basic mesh with advanced customisation options and high-accuracy rendered point colours
Radar4Motion: 4D Imaging Radar based IMU-free Odometry with Radar Cross Section (RCS) weighted Correspondences
Convert various AEC model formats for efficient viewing in the browser with xeokit.
[NeurIPS 2024 D&B] Point Cloud Matters: Rethinking the Impact of Different Observation Spaces on Robot Learning
[ICLR 2025] From anything to mesh like human artists. Official impl. of "MeshAnything: Artist-Created Mesh Generation with Autoregressive Transformers"
3DGS-to-PC: Convert a 3D gaussian splatting scene into a dense point cloud or basic mesh with advanced customisation options and high-accuracy rendered point colours
💫 [CVPR 2024] LiDAR4D: Dynamic Neural Fields for Novel Space-time View LiDAR Synthesis
[ICLR 2025] From anything to mesh like human artists. Official impl. of "MeshAnything: Artist-Created Mesh Generation with Autoregressive Transformers"
Pointcept: a codebase for point cloud perception research. Latest works: PTv3 (CVPR'24 Oral), PPT (CVPR'24), OA-CNNs (CVPR'24), MSC (CVPR'23)
OpenMMLab's next-generation platform for general 3D object detection.
PointNet and PointNet++ implemented by pytorch (pure python) and on ModelNet, ShapeNet and S3DIS.
[ICLR 2025] From anything to mesh like human artists. Official impl. of "MeshAnything: Artist-Created Mesh Generation with Autoregressive Transformers"
3DGS-to-PC: Convert a 3D gaussian splatting scene into a dense point cloud or basic mesh with advanced customisation options and high-accuracy rendered point colours
[CVPR 2024] Dynamic Adapter Meets Prompt Tuning: Parameter-Efficient Transfer Learning for Point Cloud Analysis
💫 [CVPR 2024] LiDAR4D: Dynamic Neural Fields for Novel Space-time View LiDAR Synthesis
[ECCV'24] SeFlow: A Self-Supervised Scene Flow Method in Autonomous Driving