Datasets › Virtual Gallery
Virtual Gallery
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/
Benchmarks archive 2025-07-28
No leaderboard in the archive resolves to this dataset.
Papers archive 2025-07-28
No paper in the archive has a leaderboard row on this dataset; the archive counts 2 papers for it but never published that list.
Dataset loaders archive 2025-07-28
No loader listed in the archive.
Tasks archive 2025-07-28
License archive 2025-07-28
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Modalities archive 2025-07-28
No modality tagged.
Languages archive 2025-07-28
No language tagged.
Variants archive 2025-07-28
- Virtual Gallery
1 variant name, as the archive lists them.
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