Papers With Code 2 | ML Benchmarks, SotA Results & Code

The Virtual Gallery dataset is a synthetic dataset that targets multiple challenges such as varying lighting conditions and different occlusion levels for various tasks such as depth estimation, instance segmentation and visual localization.

It consists of a scene containing 3-4 rooms, in which a total of 42 free-for-use famous paintings are placed on the walls.

The virtual model and the captured images were generated with Unity software, allowing us to extract ground-truth information such as depth, semantic and instance segmentation, 2D-2D and 2D-3D correspondences.

Source: Visual Localization by Learning Objects-Of-Interest Dense Match Regression Image Source: https://europe.naverlabs.com/research/3d-vision/virtual-gallery-dataset/