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Simultaneous Multi-class Pixel Labeling over Coherent Image Sets

Date

Authors

Rivera, Paul

Gould, Stephen

Publisher

IEEE Communications Society

Abstract

Multi-class pixel labeling is an important problem in computer vision that has many diverse applications, including interactive image segmentation, semantic and geometric scene understanding, and stereo reconstruction. Current state-of-the-art approaches

Keywords

Keywords: Baseline models; Coherent images; Contextual information; Data sets; Diverse applications; Interactive image segmentation; markov random field; Multi-class; Scene understanding; Semi-supervised; State-of-the-art approach; Stereo reconstruction; Test sets; image segmentation; markov random field; pixel labeling

URI

http://hdl.handle.net/1885/39504

Collections

ANU Research Publications

Source

A Novel Illumination-Invariant Loss for Monocular 3D Pose Estimation

Type

Conference paper

DOI

10.1109/DICTA.2011.24

Restricted until

2037-12-31

Downloads

File

Description

01_Rivera_Simultaneous_Multi-class_Pixel_2011.pdf (1.88 MB)