Recent research in visual inference from monocular images has shown that discriminatively trained image-based predictors can provide fast, automatic qualitative 3D reconstructions...
Atul Kanaujia, Cristian Sminchisescu, Dimitris N. ...
We present a random field based model for stereo vision with explicit occlusion labeling in a probabilistic framework. The model employs non-parametric cost functions that can be ...
We introduce a novel image segmentation algorithm that uses translational symmetry as the primary foreground/background separation cue. We investigate the process of identifying a...
Yanxi Liu, Tamara Belkina, James Hays, Roberto Lub...
We introduce a generalized representation for a boosted classifier with multiple exit nodes, and propose a method to training which combines the idea of propagating scores across ...
In this paper we present a novel boosting algorithm for supervised learning that incorporates invariance to data transformations and has high generalization capabilities. While on...