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Higher Order Priors for Joint Intrinsic Image, Objects, and Attributes Estimation
Vibhav Vineet · Carsten Rother · Philip Torr

Sun Dec 08 02:00 PM -- 06:00 PM (PST) @ Harrah's Special Events Center, 2nd Floor

Many methods have been proposed to recover the intrinsic scene properties such as shape, reflectance and illumination from a single image. However, most of these models have been applied on laboratory datasets. In this work we explore the synergy effects between intrinsic scene properties recovered from an image, and the objects and attributes present in the scene. We cast the problem in a joint energy minimization framework; thus our model is able to encode the strong correlations between intrinsic properties (reflectance, shape, illumination), objects (table, tv-monitor), and materials (wooden, plastic) in a given scene. We tested our approach on the NYU and Pascal datasets, and observe both qualitative and quantitative improvements in the overall accuracy.

Author Information

Vibhav Vineet (Oxford Brookes University)
Carsten Rother (TU Dresden)
Philip Torr (University of Oxford)

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