Trending repositories for topic point-cloud
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.
Draco is a library for compressing and decompressing 3D geometric meshes and point clouds. It is intended to improve the storage and transmission of 3D graphics.
💫 [CVPR 2024] LiDAR4D: Dynamic Neural Fields for Novel Space-time View LiDAR Synthesis
User-friendly, commercial-grade software for processing aerial imagery. 🛩
PointNet and PointNet++ implemented by pytorch (pure python) and on ModelNet, ShapeNet and S3DIS.
Patchwork++: Fast and robust ground segmentation method for 3D LiDAR scans. @ IROS'22
:thought_balloon: Diffusion Probabilistic Models for 3D Point Cloud Generation (CVPR 2021)
A PyTorch implementation of Dynamic Graph CNN for Learning on Point Clouds (DGCNN)
Photogrammetry Guide. Photogrammetry is widely used for Aerial surveying, Agriculture, Architecture, 3D Games, Robotics, Archaeology, Construction, Emergency management, and Medical.
A collection of GICP-based fast point cloud registration algorithms
A BVH implementation to speed up raycasting and enable spatial queries against three.js meshes.
A command line toolkit to generate maps, point clouds, 3D models and DEMs from drone, balloon or kite images. 📷
Reconstructing compact building models from point clouds using deep implicit fields [ISPRS 2022]
💫 [CVPR 2024] LiDAR4D: Dynamic Neural Fields for Novel Space-time View LiDAR Synthesis
30th June, 2019 - 30th June, 2020. Robotics and Machine Intelligence Lab, The Hong Kong Polytechnic University. This work is supported in part by the Chinese National Engineering Research Centre for S...
Reconstructing compact building models from point clouds using deep implicit fields [ISPRS 2022]
Source code for the article "GroundGrid: LiDAR Point Cloud Ground Segmentation and Terrain Estimation"
A ground segmentation algorithm for 3D point clouds based on the work described in “Fast segmentation of 3D point clouds: a paradigm on LIDAR data for Autonomous Vehicle Applications”, D. Zermas, I. I...
Patchwork++: Fast and robust ground segmentation method for 3D LiDAR scans. @ IROS'22
:thought_balloon: Diffusion Probabilistic Models for 3D Point Cloud Generation (CVPR 2021)
Pointcept: a codebase for point cloud perception research. Latest works: PTv3 (CVPR'24 Oral), PPT (CVPR'24), OA-CNNs (CVPR'24), MSC (CVPR'23)
A PyTorch implementation of Dynamic Graph CNN for Learning on Point Clouds (DGCNN)
[ICCV2023] Official Implementation of "UniTR: A Unified and Efficient Multi-Modal Transformer for Bird’s-Eye-View Representation"
C++ library and programs for reading and writing ASPRS LAS format with LiDAR data
[ROS package] Lightweight and Accurate Point Cloud Clustering
Photogrammetry Guide. Photogrammetry is widely used for Aerial surveying, Agriculture, Architecture, 3D Games, Robotics, Archaeology, Construction, Emergency management, and Medical.
Accompanying library for the Record3D iOS app (https://record3d.app/). Allows you to receive RGBD stream from iOS devices with TrueDepth camera(s).
A collection of GICP-based fast point cloud registration algorithms
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 and PointNet++ implemented by pytorch (pure python) and on ModelNet, ShapeNet and S3DIS.
Tooling for professional robotic development in C++ and Python with a touch of ROS, autonomous driving and aerospace.
💫 [CVPR 2024] LiDAR4D: Dynamic Neural Fields for Novel Space-time View LiDAR Synthesis
A collection of GICP-based fast point cloud registration algorithms
Source code for the article "GroundGrid: LiDAR Point Cloud Ground Segmentation and Terrain Estimation"
User-friendly, commercial-grade software for processing aerial imagery. 🛩
A command line toolkit to generate maps, point clouds, 3D models and DEMs from drone, balloon or kite images. 📷
Draco is a library for compressing and decompressing 3D geometric meshes and point clouds. It is intended to improve the storage and transmission of 3D graphics.
A BVH implementation to speed up raycasting and enable spatial queries against three.js meshes.
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
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...
💫 [CVPR 2024] LiDAR4D: Dynamic Neural Fields for Novel Space-time View LiDAR Synthesis
Source code for the article "GroundGrid: LiDAR Point Cloud Ground Segmentation and Terrain Estimation"
3D Pose Estimation of Two Interacting Hands from a Monocular Event Camera [3DV'24]
Using the KITTI dataset, we employed Open3D to visualize, downsample, segment with RANSAC, cluster via DBSCAN, create 3D bounding boxes, and perform surface reconstruction on point clouds.
Official repository for paper "Attention-based Point Cloud Edge Sampling" (APES), Highlight@CVPR 2023
Python efficient farthest point sampling (FPS) library. Compatible with numpy.
30th June, 2019 - 30th June, 2020. Robotics and Machine Intelligence Lab, The Hong Kong Polytechnic University. This work is supported in part by the Chinese National Engineering Research Centre for S...
Efficient Online Segmentation of Ground&Wall Points for Multi-line Spinning LiDARs. //在线分割激光点云中的地面点和墙面点。
Reconstructing compact building models from point clouds using deep implicit fields [ISPRS 2022]
Pointcept: a codebase for point cloud perception research. Latest works: PTv3 (CVPR'24 Oral), PPT (CVPR'24), OA-CNNs (CVPR'24), MSC (CVPR'23)
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...
A ground segmentation algorithm for 3D point clouds based on the work described in “Fast segmentation of 3D point clouds: a paradigm on LIDAR data for Autonomous Vehicle Applications”, D. Zermas, I. I...
Papers, code and datasets about deep learning for 3D Object Detection.
Patchwork++: Fast and robust ground segmentation method for 3D LiDAR scans. @ IROS'22
OpenMMLab's next-generation platform for general 3D object detection.
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)
A BVH implementation to speed up raycasting and enable spatial queries against three.js meshes.
Tooling for professional robotic development in C++ and Python with a touch of ROS, autonomous driving and aerospace.
Draco is a library for compressing and decompressing 3D geometric meshes and point clouds. It is intended to improve the storage and transmission of 3D graphics.
User-friendly, commercial-grade software for processing aerial imagery. 🛩
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
A command line toolkit to generate maps, point clouds, 3D models and DEMs from drone, balloon or kite images. 📷
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...
A collection of GICP-based fast point cloud registration algorithms
💫 [CVPR 2024] LiDAR4D: Dynamic Neural Fields for Novel Space-time View LiDAR Synthesis
Using the KITTI dataset, we employed Open3D to visualize, downsample, segment with RANSAC, cluster via DBSCAN, create 3D bounding boxes, and perform surface reconstruction on point clouds.
Shape-Guided Dual-Memory Learning for 3D Anomaly Detection [ICML2023]
Source code for the article "GroundGrid: LiDAR Point Cloud Ground Segmentation and Terrain Estimation"
3D Pose Estimation of Two Interacting Hands from a Monocular Event Camera [3DV'24]
3D object reconstruction with multi-view RGB-D images.
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...
Python efficient farthest point sampling (FPS) library. Compatible with numpy.
[NeurIPS 2023] Offical code for <Real3D-AD: A Dataset of Point Cloud Anomaly Detection>. A 3D point cloud anomaly detection dataset and benchmark.
[RA-L 2023] Official Repository of "Spectral Geometric Verification: Re-Ranking Point Cloud Retrieval for Metric Localization", RA-L, Volume 8, Issue 5, May 2023
Pointcept: a codebase for point cloud perception research. Latest works: PTv3 (CVPR'24 Oral), PPT (CVPR'24), OA-CNNs (CVPR'24), MSC (CVPR'23)
Official implementation of the paper "ACL-SPC: Adaptive Closed-Loop system for Self-Supervised Point Cloud Completion" (CVPR 2023)
Official repository for paper "Attention-based Point Cloud Edge Sampling" (APES), Highlight@CVPR 2023
A curated list of Place Recognition methods, datasets, and various algorithms for LiDAR
[CVPR2022] Geometric Transformer for Fast and Robust Point Cloud Registration
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...
[arXiv 2023] PointLLM: Empowering Large Language Models to Understand Point Clouds
[ICCV2023] Official Implementation of "UniTR: A Unified and Efficient Multi-Modal Transformer for Bird’s-Eye-View Representation"
[CVPR 2024] Dynamic Adapter Meets Prompt Tuning: Parameter-Efficient Transfer Learning for Point Cloud Analysis
Building Volumetric Beliefs for Dynamic Environments Exploiting Map-Based Moving Object Segmentation (RAL 2023)
💫 [CVPR 2024] LiDAR4D: Dynamic Neural Fields for Novel Space-time View LiDAR Synthesis
Source code for the article "GroundGrid: LiDAR Point Cloud Ground Segmentation and Terrain Estimation"
DistillBEV: Boosting Multi-Camera 3D Object Detection with Cross-Modal Knowledge Distillation (ICCV 2023)
3D-OWIS is capable of detecting unknown instances in inference, and progressively learning novel classes in the process of training.
A curated list of Place Recognition methods, datasets, and various algorithms for LiDAR
(CVPR 2023) MarS3D: A Plug-and-Play Motion-Aware Model for Semantic Segmentation on Multi-Scan 3D Point Clouds
[CVPR 2024, highlight] Living Scenes: Multi-object Relocalization and Reconstruction in Changing 3D Environments
PatchAugNet: Patch feature augmentation-based heterogeneous point cloud place recognition in large-scale street scenes
Using PyTorch's MiDaS model and Open3D's point cloud to map a scene in 3D 🏞️🔭
OpenMMLab's next-generation platform for general 3D object detection.
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)
Draco is a library for compressing and decompressing 3D geometric meshes and point clouds. It is intended to improve the storage and transmission of 3D graphics.
A BVH implementation to speed up raycasting and enable spatial queries against three.js meshes.
Tooling for professional robotic development in C++ and Python with a touch of ROS, autonomous driving and aerospace.
A command line toolkit to generate maps, point clouds, 3D models and DEMs from drone, balloon or kite images. 📷
User-friendly, commercial-grade software for processing aerial imagery. 🛩
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: Deep Learning on Point Sets for 3D Classification and Segmentation
[CVPR 2024] Dynamic Adapter Meets Prompt Tuning: Parameter-Efficient Transfer Learning for Point Cloud Analysis
[ICCV2023] Official Implementation of "UniTR: A Unified and Efficient Multi-Modal Transformer for Bird’s-Eye-View Representation"
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...
[ICML'23 Oral] Learning Signed Distance Functions from Noisy 3D Point Clouds via Noise to Noise Mapping
💫 [CVPR 2024] LiDAR4D: Dynamic Neural Fields for Novel Space-time View LiDAR Synthesis
[NeurIPS 2023] Offical code for <Real3D-AD: A Dataset of Point Cloud Anomaly Detection>. A 3D point cloud anomaly detection dataset and benchmark.
[arXiv 2023] PointLLM: Empowering Large Language Models to Understand Point Clouds
PatchAugNet: Patch feature augmentation-based heterogeneous point cloud place recognition in large-scale street scenes
A curated list of Place Recognition methods, datasets, and various algorithms for LiDAR
Auto-labeling of point cloud sequences for 3D object detection using an ensemble of experts and temporal refinement
This is the official repo for Contextual Point Cloud Modeling for Weakly-supervised Point Cloud Semantic Segmentation (ICCV 23).
3D Pose Estimation of Two Interacting Hands from a Monocular Event Camera [3DV'24]
official code of “OpenShape: Scaling Up 3D Shape Representation Towards Open-World Understanding”
Official repository for paper "Attention-based Point Cloud Edge Sampling" (APES), Highlight@CVPR 2023
Benchmarking Robustness of 3D Object Detection to Common Corruptions in Autonomous Driving, CVPR 2023
Building Volumetric Beliefs for Dynamic Environments Exploiting Map-Based Moving Object Segmentation (RAL 2023)
Pointcept: a codebase for point cloud perception research. Latest works: PTv3 (CVPR'24 Oral), PPT (CVPR'24), OA-CNNs (CVPR'24), MSC (CVPR'23)
Cross platform 3D renderer in C++ and OpenGL with lighting, shadows and materials.