English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
 
 
DownloadE-Mail
 Local TagsRelease HistoryDetailsSummary
  Two stream network for stroke detection in table tennis

Zahra, A., & Martin, P.-E. (2021). Two stream network for stroke detection in table tennis. In Proceedings of MediaEval 2021: Multimedia Benchmark Workshop. doi:10.48550/arXiv.2112.12073.

Item is

 

show all hide all

Basic

show hide
Item Permalink: https://hdl.handle.net/21.11116/0000-000A-4B11-F Version Permalink: https://hdl.handle.net/21.11116/0000-000B-FE95-F
Genre: Conference Paper

Files

show Files
hide Files
:
Zahra_Two_MediaEval_2021.pdf (Any fulltext), 666KB
View   Save
File Permalink:
https://hdl.handle.net/21.11116/0000-000A-4B23-B
Name:
Zahra_Two_MediaEval_2021.pdf
Description:
-
OA-Status:
Miscellaneous
Visibility:
Public
MIME-Type / Checksum:
application/pdf / [MD5]
Technical Metadata:
View
Copyright Date:
2021
Copyright Info:
Copyright 2021 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
License:
https://creativecommons.org/licenses/by/4.0/

Locators

show

Creators

show
hide
 Creators:
Zahra, Anam1, Author                 
Martin, Pierre-Etienne1, Author                 
Affiliations:
1Department of Comparative Cultural Psychology, Max Planck Institute for Evolutionary Anthropology, Max Planck Society, ou_3040267              

Content

show
hide
Free keywords: Computer Science, Computer Vision and Pattern Recognition, cs.CV,Computer Science, Learning, cs.LG,Computer Science, Multimedia, cs.MM
 Abstract: This paper presents a table tennis stroke detection method from videos. The
method relies on a two-stream Convolutional Neural Network processing in
parallel the RGB Stream and its computed optical flow. The method has been
developed as part of the MediaEval 2021 benchmark for the Sport task. Our
contribution did not outperform the provided baseline on the test set but has
performed the best among the other participants with regard to the mAP metric.

Details

show
hide
Language(s): eng - English
 Dates: 2021-12-16
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.48550/arXiv.2112.12073
Other: hal-03482217
 Degree: -

Event

show
hide
Title: MediaEval 2021 Workshop
Place of Event: Online
Start-/End Date: 2021-12-13 - 2021-12-15

Legal Case

show

Project information

show

Source 1

show
hide
Title: Proceedings of MediaEval 2021 : Multimedia Benchmark Workshop
Source Genre: Proceedings
 Creator(s):
Affiliations:
Publ. Info: -
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: - Identifier: URN: https://multimediaeval.github.io/editions/2021/