50 datasets found

The Waymo Open dataset is a large-scale video dataset used for testing object-centric video models.

STPLS3D: A large-scale synthetic and real aerial photogrammetry 3D point cloud dataset

Real and synthesized mmWave radar data, ground truth 2D depth images and point clouds for 3DRIMR experiments

The dataset used in the paper for surface reconstruction from point clouds.

The dataset used in the paper is a collection of 2D and 3D point clouds, each representing a different shape (e.g. unit circle, unit disk, unit sphere, unit ball, Stanford...

The Mip-NeRF 360 and Tanks & Temples datasets are used to evaluate the performance of the Pixel-GS method.

Uni3DL is a unified model for 3D and language understanding. It operates directly on point clouds and supports diverse 3D vision-language tasks, including semantic segmentation,...

A dataset of 1000 3D models, used for testing the robustness of surface reconstruction methods.

TUM-MLS-2016: An annotated mobile lidar dataset of the TUM City Campus for semantic point cloud interpretation in urban areas.

Developing and testing robust autonomy: The university of sydney campus data set.

3D ShapeNets: A Deep Representation for Volumetric Shapes.

Point-BERT is a new paradigm for learning point cloud Transformers. It pre-trains standard point cloud Transformers with a Masked Point Modeling (MPM) task.

Semantic segmentation and 3D detection tasks on PartNet and ScanNet datasets

The SUNRGB-D dataset features 5,285 training and 5,050 test samples from multiple RGB-D cameras. The dataset provides annotations for the first 37 NYUv2 semantic classes and for...

3D object detection datasets, ScanNet and SUNRGB-D

3D object detection is one of the most important tasks in autonomous driving and robotics. Our research focuses on tackling low efficiency issue of point-based methods on...

ULIP: Learning a unified representation of language, images, and point clouds for 3D understanding

The dataset used for training a Convolutional Neural Network to predict a grasp quality score over all grasp poses, given a depth image of an object.

The Argoverse 2 motion forecasting dataset contains 250,000 driving scenarios, each 11 seconds long. These scenarios cover 6 geographical regions and represent 763 total hours...

A Point-Cloud Deep Learning Framework for Prediction of Fluid Flow Fields on Irregular Geometries