Discriminative Learning with Latent Variables for Cluttered Indoor Scene Understanding
We address the problem of understanding an indoor scene from a single image in terms of recovering the layouts of the faces (floor, ceiling, walls) and furniture. A major challenge of this task arises from the fact that most indoor scenes are cluttered by furniture and decorations, whose appearances vary drastically across scenes, and can hardly be modeled (or even hand-labeled) consistently. In this paper we tackle this problem by introducing latent variables to account for clutters, so that...[Show more]
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|Source:||Proceedings of the European Conference on Computer Vision (ECCV 2010)|
|01_Wang_Discriminative_Learning_with_2010.pdf||3.54 MB||Adobe PDF||Request a copy|
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