[go: up one dir, main page]
loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Affiliation

Select a Subject

Valeo Vision Systems, Valeo Ireland and Ireland
Context (please use complete words only)
Field
Sort by

1 Papers

Design of Real-time Semantic Segmentation Decoder for Automated Driving

Topics: Segmentation and Grouping; Machine Learning Technologies for Vision; Deep Learning for Visual Understanding

Authors: Arindam Das 1 , Saranya Kandan 1 , Senthil Yogamani 2 and Pavel Křížek 3

Affiliations: 1 Detection Vision Systems, Valeo India and India , 2 Valeo Vision Systems, Valeo Ireland and Ireland , 3 Valeo R&D DVS, Prague and Czech Republic

Digital Object Identifier: 10.5220/0007366003930400

Proceedings of VISAPP 2019/VISIGRAPP, ISBN: 978-989-758-354-4

Collapse Button Quick Abstract
Semantic segmentation remains a computationally intensive algorithm for embedded deployment even with the rapid growth of computation power. Thus efficient network design is a critical aspect especially for applications like automated driving which requires real-time performance. Recently, there has been a lot of research on designing efficient encoders that are mostly task agnostic. Unlike image classification and bounding box object detection tasks, decoders are computationally expensive as well for semantic segmentation task. In this work, we focus on efficient design of the segmentation decoder and assume that an efficient encoder is already designed to provide shared features for a multi-task learning system. We design a novel efficient non-bottleneck layer and a family of decoders which fit into a small run-time budget using VGG10 as efficient encoder. We demonstrate in our dataset that experimentation with various design choices led to an improvement of 10% from a baseline performance.
Collapse Button Related Ontology Subjects/Areas/Topics (3)
Computer Vision, Visualization and Computer Graphics

Image and Video Analysis

Segmentation and Grouping

Topic(s):

Filter listed results, by
Author
Locate Author in list below
Add Author(s) to filter:

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic