57 datasets found

The NYU DublinCity LiDAR dataset is a high resolution collection of 41 LiDAR scans over an area of Dublin, Ireland.

The dataset used in the paper is ScanNet20, a subset of the ScanNet dataset, and ScanNet200, another subset of the ScanNet dataset.

The dataset used in the paper is ScanNet, a large-scale dataset of 3D indoor scenes, and S3DIS, a dataset of 3D indoor scenes with semantic labels.

Surface reconstruction from complex scenes.

Surface reconstruction from real point cloud scans.

Surface reconstruction from raw point clouds.

Implicit filtering on SDFs to reduce the noise of the signed distance field while preserving geometry features.

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