Datasets › Virtual Gallery

Virtual Gallery

Introduced by Philippe Weinzaepfel et al. in Visual Localization by Learning Objects-Of-Interest Dense Match Regression archive 2025-07-28

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

No licence recorded in the archive. Absence here is not a statement about the dataset's terms.

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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