3D Feature Matching

The 3DMATCH benchmark evaluates how well descriptors (both 2D and 3D) can establish correspondences between RGB-D frames of different views. The dataset contains 2D RGB-D patches and 3D patches (local TDF voxel grid volumes) of wide-baselined correspondences. The pixel size of each 2D patch is determined by the projection of the 0.3m3 local 3D patch around the interest point onto the image plane. Source: 3DMatch: Learning Local Geometric Descriptors from RGB-D Reconstructions

Dataset produced for the SAPIEN simulation environment. From the website: "PartNet-Mobility dataset is a collection of 2K articulated objects with motion annotations and rendernig material. The dataset powers research for generalizable computer vision and manipulation. The dataset is a continuation of ShapeNet and PartNet. "

DeformingThings4D is a synthetic dataset containing 1,972 animation sequences spanning 31 categories of humanoids and animals. It provides 200 animations for humanoids and 1772 animations for animals. #### Use case of the dataset The dataset is designed to tackle the following tasks using data-driven approaches: - Scene flow estimation - Non-rigid tracking/registration - Shape and motion completion - Learning riggings from observation - Generic non-rigid reconstruction Source: DeformingThings4D dataset Image source: DeformingThings4D dataset

A benchmark for matching and registration of partial point clouds with time-varying geometry. It is constructed using randomly selected 1761 sequences from DeformingThings4D.

CPNet dataset has a collection of 25 categories, 2,334 models based on ShapeNetCore, which includes 1,000+ correspondence sets with 104,861 points.