OASIS: A Large-Scale Dataset for Single Image 3D in the Wild
This provides a large-scale dataset to advance 3D vision research, addressing a data bottleneck for researchers in computer vision.
The authors tackled the problem of limited data for single-view 3D reconstruction by introducing OASIS, a dataset with detailed 3D geometry annotations for 140,000 images, and they trained and evaluated leading models on various tasks.
Single-view 3D is the task of recovering 3D properties such as depth and surface normals from a single image. We hypothesize that a major obstacle to single-image 3D is data. We address this issue by presenting Open Annotations of Single Image Surfaces (OASIS), a dataset for single-image 3D in the wild consisting of annotations of detailed 3D geometry for 140,000 images. We train and evaluate leading models on a variety of single-image 3D tasks. We expect OASIS to be a useful resource for 3D vision research. Project site: https://pvl.cs.princeton.edu/OASIS.