Abstract: We present in this paper an interactive approach for semantically modeling the indoor environment given only a single indoor image as input, without requiring access to the scene or using any additional measurements like RGBD cameras. Our key insight is that, although depth estimation from a single image is notoriously difficult, we can conveniently obtain a relatively accurate normal map, which essentially conveys a great deal of scene geometry. This enables us to model each object in a data-driven manner by representing the object as a normal...
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Topics: 
Computer vision
Artificial intelligence