We propose a novel method to synthesize intermediate views from two stereo images and disparity maps that is robust to errors in disparity map. The proposed method computes a plac...
We present MI-CRF, a conditional random field (CRF) model for multiple instance learning (MIL). MI-CRF models bags as nodes in a CRF with instances as their states. It combines di...
We investigate maximum likelihood parameter learning in Conditional Random Fields (CRF) and present an empirical study of pseudo-likelihood (PL) based approximations of the paramet...
This paper proposes a computational system of object categorization based on decomposition and adaptive fusion of visual information. A coupled Conditional Random Field is develop...
This paper presents a semi-supervised training method for linear-chain conditional random fields that makes use of labeled features rather than labeled instances. This is accompli...