Higher order priors for joint intrinsic image, objects, and attributes estimation

Conference item

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.

Authors: Vineet, V; Rother, C; Torr, PHS

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Curran Associates
• Host title: Advances in Neural Information Processing Systems 26 (NIPS 2013)
• Volume: 1
• Pages: 557-565
• Publication date: 2014-04-01
• Acceptance date: 2013-09-05
• Event title: 27th Annual Conference on Neural Information Processing Systems 2013 (NeurIPS 2013)
• Event location: Lake Tahoe, Nevada, USA
• Event website: https://neurips.cc/Conferences/2013
• Event start date: 2013-12-05
• Event end date: 2013-12-10
• ISSN: 1049-5258
• ISBN: 9781632660244
• Language: English