35 datasets found

SynthCity: A large scale synthetic point cloud dataset for pre-training deep learning models, enabling generalisation and expansion of their usage to real-world data.

The dataset used in the paper is a collection of unpaired shapes, including chairs and tables, and letters in different font styles.

The MPEG 8i dataset contains 6 voxelized point cloud models.

3D computer vision models are commonly used in security-critical applications such as autonomous driving and surgical robotics. Emerging concerns over the robustness of these...

A large-scale point cloud classification benchmark, focusing on semantic segmentation of urban scenes.

SEED is a 3D DETR framework for detecting 3D objects from point clouds. It involves a dual query selection module and a deformable grid attention module.

RadHAR dataset

Pantomime dataset

Upper Body Point Cloud Gestures (UBPG) RGB-D gesture point cloud dataset

Gesture recognition interface for point clouds generated by mmWave Radars

The VoxelNet dataset is a large-scale dataset for 3D object detection, consisting of 3D point clouds and corresponding annotations.

Zero-shot learning (ZSL) aims to classify objects that are not observed or seen during training. It relies on class semantic description to transfer knowledge from the seen...

The Point Completion Network (PCN) dataset is a large-scale, multi-category dataset for shape completion. It contains pairs of partial and complete point clouds, where the...

The dataset used in the paper is a real-world 3D point cloud dataset, which is used for 3D shape classification, part segmentation, and shape retrieval tasks.

Point cloud registration is a crucial problem in computer vision and robotics. Existing methods either rely on matching local geometric features, which are sensitive to the pose...