Maximum a posteriori (MAP) inference in Markov Random Fields (MRFs) is an NP-hard problem, and thus research has focussed on either finding efficiently solvable subclasses (e.g. t...
Dhruv Batra, Andrew Gallagher, Devi Parikh, Tsuhan...
This paper presents a method for joint stereo matching and object segmentation. In our approach a 3D scene is represented as a collection of visually distinct and spatially cohere...
Michael Bleyer, Carsten Rother, Pushmeet Kohli, Da...
In this paper, we propose a novel framework to jointly recover the illumination environment and an estimate of the cast shadows in a scene from a single image, given coarse 3D geo...
Modern machine learning techniques provide robust approaches for data-driven modeling and critical information extraction, while human experts hold the advantage of possessing hig...
The emergence of low-cost sensing architectures for diverse modalities has made it possible to deploy sensor networks that capture a single event from a large number of vantage po...
Mark A. Davenport, Chinmay Hegde, Marco F. Duarte,...