Abstract
The papers in this special section address the programs and services supported by graphical models in computer vision. This section explores the main challenges in this framework-modeling novel priors, learning, inference-and presents innovative solutions. The papers cover the aspects of modeling novel priors, inference algorithms and parameter learning methods in the context of higher order graphical models.
Cite
CITATION STYLE
Alahari, K., Batra, D., Ramalingam, S., Paragios, N., & Zemel, R. (2015, July 1). Guest Editors’ Introduction: Special Section on Higher Order Graphical Models in Computer Vision. IEEE Transactions on Pattern Analysis and Machine Intelligence. IEEE Computer Society. https://doi.org/10.1109/TPAMI.2015.2434651
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