English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
Add to Basket
 Local TagsRelease HistoryDetailsSummary
  Spatio-temporal CNN baseline method for the sports video task of MediaEval 2021 benchmark

Martin, P.-E. (2021). Spatio-temporal CNN baseline method for the sports video task of MediaEval 2021 benchmark. In Proceedings MediaEval 2021: Multimedia Benchmark Workshop.

Item is

 

show all hide all

Basic

show hide
Item Permalink: https://hdl.handle.net/21.11116/0000-000A-4B39-3 Version Permalink: https://hdl.handle.net/21.11116/0000-000B-941D-E
Genre: Conference Paper

Files

show Files
hide Files
:
Martin_Spatio-Temporal_MediaEval_2021.pdf (Any fulltext), 3MB
View   Save
File Permalink:
https://hdl.handle.net/21.11116/0000-000A-4B3B-1
Name:
Martin_Spatio-Temporal_MediaEval_2021.pdf
Description:
-
OA-Status:
Miscellaneous
Visibility:
Public
MIME-Type / Checksum:
application/pdf / [MD5]
Technical Metadata:
View
Copyright Date:
2021
Copyright Info:
HAL is a multi-disciplinary open access archive for the deposit and dissemination of sci- entific research documents, whether they are pub- lished or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers.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:
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 the baseline method proposed for the Sports Video task part of the MediaEval 2021 benchmark. This task proposes a stroke detection and a stroke classification subtasks. This baseline addresses both subtasks. The spatio-temporal CNN architecture and the training process of the model are tailored according to the addressed subtask. The method has the purpose of helping the participants to solve the task and is not meant to reach stateof-the-art performance. Still, for the detection task, the baseline is performing better than the other participants, which stresses the difficulty of such a task.

Details

show
hide
Language(s): eng - English
 Dates: 2021-12-16
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: Other: hal-03482222
 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 MediaEval 2021 : Multimedia Benchmark Workshop
Source Genre: Proceedings
 Creator(s):
Affiliations:
Publ. Info: -
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: - Identifier: URN: https://2021.multimediaeval.com/