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MIT Indoor Scene Recognition Computer Vision Project

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Indoor Scene Recognition

Examples of Images 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.


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.


A. Quattoni, and A.Torralba. Recognizing Indoor Scenes. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2009.


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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2 years ago

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airport_inside artstudio auditorium bakery bar bathroom bedroom bookstore bowling buffet casino children_room church_inside classroom cloister closet clothingstore computerroom concert_hall corridor deli dentaloffice dining_room elevator fastfood_restaurant florist gameroom garage greenhouse grocerystore gym hairsalon hospitalroom inside_bus inside_subway jewelleryshop kindergarden kitchen laboratorywet laundromat library livingroom lobby locker_room mall meeting_room movietheater museum nursery office operating_room pantry poolinside prisoncell restaurant restaurant_kitchen shoeshop stairscase studiomusic subway toystore trainstation tv_studio videostore waitingroom warehouse winecellar