Datasets › MIT Indoor Scenes
MIT Indoor Scenes
Context This is the Original data provided by MIT .
Indoor scene recognition is a challenging open problem in high level vision. Most scene recognition models that work well for outdoor scenes perform poorly in the indoor domain. The main difficulty is that while some indoor scenes (e.g. corridors) can be well characterized by global spatial properties, others (e.g., bookstores) are better characterized by the objects they contain. More generally, to address the indoor scenes recognition problem we need a model that can exploit local and global discriminative information.
Content The database contains 67 Indoor categories, and a total of 15620 images. The number of images varies across categories, but there are at least 100 images per category. All images are in jpg format. The images provided here are for research purposes only.
Acknowledgements Thanks to MIT Thanks to Aude Oliva for helping to create the database of indoor scenes. Funding for this research was provided by NSF Career award (IIS 0747120)
Benchmarks archive 2025-07-28
All 1 leaderboard whose dataset resolves to this page shown (sort by any header). "First row" is the archive's own first row at snapshot, in the archive's row order; nothing here re-ranks and metric direction is not asserted.
| First row (archive order) | Paper | Code | ||||
|---|---|---|---|---|---|---|
| Scene Recognition | MIT Indoor Scenes | FOSNet Accuracy 90.3 | FOSNet: An End-to-End Trainable Deep Neural Network for... | — | 3 | Compare |
Papers archive 2025-07-28
3 shown of 3 papers with a leaderboard row on this dataset's benchmarks, newest first. The archive's own "papers using this dataset" list was never published, so this is the benchmark-backed subset; the archive's count for this dataset is 9. The Syntology column is from Syntology's graph (read 2026-09-24), stated per sample; it is not part of any archive number.
| Date | Samples run Syntology | |||
|---|---|---|---|---|
| SRRM: Semantic Region Relation Model for Indoor Scene Recognition | 1 | 1 | 15 May 2023 | not harvested |
| Semantic-Aware Scene Recognition | 1 | 1 | 5 Sep 2019 | ran 0 of 3 samples (3 unverified) |
| FOSNet: An End-to-End Trainable Deep Neural Network for Scene Recognition | 0 | 1 | 17 Jul 2019 | not harvested |
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
- MIT Indoor Scenes
1 variant name, as the archive lists them.
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