3D-Point-Clouds

HuangCongQing/3D-Point-Clouds is ranked 15,787 among these 8 peers; Little-Podi/Collaborative_Perception is ranked 15,789.

[** **] [ShapeNet] A collaborative dataset between researchers at Princeton, Stanford and TTIC. [** **] [PartNet] The PartNet dataset provides fine grained part annotation of objects in ShapeNetCore. [** **] [PartNet] PartNet benchmark from Nanjing University and National University of Defense Technology. [** **] ****[**S3DIS****] The Stanford Large-Scale 3D Indoor Spaces Dataset. [** ** ** **] [Stanford 3D] The Stanford 3D Scanning Repository. [** ** ** ** ** **] [Princeton Shape Benchmark] The Princeton Shape Benchmark. [SYDNEY URBAN OBJECTS DATASET] This dataset contains a variety of common urban road objects scanned with a Velodyne HDL-64E LIDAR

, collected in the CBD of Sydney, Australia. There are 631 individual scans of objects across classes of vehicles, pedestrians, signs and trees. [** ** ** **] [ASL Datasets Repository(ETH)] This site is dedicated to provide datasets for the Robotics community with the aim to facilitate result evaluations and comparisons. [** ** ** ** ** ** ** **] [Large-Scale Point Cloud Classification Benchmark(ETH)] This benchmark closes the gap and provides a large labelled 3D point cloud data set of natural scenes with over 4 billion points in total. [** **] [Robotic 3D

Scan Repository] The Canadian Planetary Emulation Terrain 3D Mapping Dataset is a collection of three-dimensional laser scans gathered at two unique planetary analogue rover test facilities in Canada. [Radish] The Robotics Data Set Repository (Radish for short) provides a collection of standard robotics data sets. [IQmulus & TerraMobilita Contest] The database contains 3D MLS data from a dense urban environment in Paris (France), composed of 300 million points. The acquisition was made in January 2013. [** ** ** ** ** **] [Oakland 3-D Point Cloud

Dataset] This repository contains labeled 3-D point cloud laser data collected from a moving platform in a urban environment. [Robotic 3D Scan Repository] This repository provides 3D point clouds from robotic experiments，log files of robot runs and standard 3D data sets for the robotics community. [Ford Campus Vision and Lidar Data Set] The dataset is collected by an autonomous ground vehicle testbed, based upon a modified Ford F-250 pickup truck. [The Stanford Track Collection] This dataset contains

about 14,000 labeled tracks of objects as observed in natural street scenes by a Velodyne HDL-64E S2 LIDAR. [PASCAL3D+] Beyond PASCAL: A Benchmark for 3D Object Detection in the Wild. [** ** ** **] [3D MNIST] The aim of this dataset is to provide a simple way to get started with 3D computer vision problems such as 3D shape recognition. [** **] [WAD] [ApolloScape] The datasets are provided by Baidu Inc. [** ** ** ** ** **] [nuScenes] The nuScenes dataset is a large-scale autonomous driving dataset. [paper] [** ** ** **] [3D

Match] Keypoint Matching Benchmark, Geometric Registration Benchmark, RGB-D Reconstruction Datasets. [** ** ** ** ** **] [BLVD] (a) 3D detection, (b) 4D tracking, (c) 5D interactive event recognition and (d) 5D intention prediction. [ICRA 2019 paper] [** ** ** ** ** ** ** **] [PedX] 3D Pose Estimation of Pedestrians, more than 5,000 pairs of high-resolution (12MP) stereo images and LiDAR data along with providing 2D and 3D labels of pedestrians. [ICRA 2019 paper] [** ** ** **] [H3D] Full-surround 3D multi-object detection and tracking dataset. [ICRA 2019 paper] [** ** ** ** ** **] [[Argoverse BY ARGO AI

]]( Two public datasets (3D Tracking and Motion Forecasting) supported by highly detailed maps to test, experiment, and teach self-driving