Improving Semantic Segmentation via Video Propagation and Label Relaxation

Semantic segmentation requires large amounts of pixel-wise annotations to learn accurate models. In this paper, we present a video prediction-based methodology to scale up training sets by synthesizing new training samples in order to improve the accuracy of semantic segmentation networks. We exploi...

Full description

Bibliographic Details

Published in:	Proceedings (IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Online) pp. 8848 - 8857
Main Authors:	Zhu, Yi, Sapra, Karan, Reda, Fitsum A., Shih, Kevin J., Newsam, Shawn, Tao, Andrew, Catanzaro, Bryan
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01.06.2019
Subjects:	Annotations Cognition Computer vision Deep Learning Grouping and Shape Image and Video Synthesis Predictive models Segmentation Semantics Training Uncertainty
ISSN:	1063-6919
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!