MIT Indoor Scene Recognition Computer Vision Project
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Indoor Scene Recognition
From the official dataset page: 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.
Database
The database contains 67 Indoor categories ... 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.
Paper
A. Quattoni, and A.Torralba. Recognizing Indoor Scenes. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2009.
Acknowledgments
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)
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Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
mit-indoor-scene-recognition_dataset,
title = { MIT Indoor Scene Recognition Dataset },
type = { Open Source Dataset },
author = { Popular Benchmarks },
howpublished = { \url{ https://universe.roboflow.com/popular-benchmarks/mit-indoor-scene-recognition } },
url = { https://universe.roboflow.com/popular-benchmarks/mit-indoor-scene-recognition },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2022 },
month = { oct },
note = { visited on 2024-12-18 },
}