Openly accessible

Black-box adversarial attacks on video recognition models

Jiang, Linxi, Ma, Xingjun, Chen, Shaoxiang, Bailey, James and Jiang, Yu-Gang 2019, Black-box adversarial attacks on video recognition models, in MM 2019 : Proceedings of the 27th ACM International Conference on Mulitmedia, ACM, [Nice, France], pp. 864-872, doi: 10.1145/3343031.3351088.

Attached Files
Name Description MIMEType Size Downloads

Title Black-box adversarial attacks on video recognition models
Author(s) Jiang, Linxi
Ma, XingjunORCID iD for Ma, Xingjun orcid.org/0000-0003-2099-4973
Chen, Shaoxiang
Bailey, James
Jiang, Yu-Gang
Conference name Multimedia. International Conference (27th : 2019 : Nice, France)
Conference location Nice, France
Conference dates 2019/10/21 - 2019/10/25
Title of proceedings MM 2019 : Proceedings of the 27th ACM International Conference on Mulitmedia
Editor(s) Unknown
Publication date 2019
Start page 864
End page 872
Total pages 9
Publisher ACM
Place of publication [Nice, France]
Keyword(s) Adversarial examples
video recognition
black-box attack
model security
ISBN 9781450368896
Language eng
DOI 10.1145/3343031.3351088
Indigenous content off
HERDC Research category E1.1 Full written paper - refereed
Free to Read? Yes
Persistent URL http://hdl.handle.net/10536/DRO/DU:30139148

Connect to link resolver
 
Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved.

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.

Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 0 times in TR Web of Science
Scopus Citation Count Cited 2 times in Scopus
Google Scholar Search Google Scholar
Access Statistics: 42 Abstract Views, 1 File Downloads  -  Detailed Statistics
Created: Tue, 16 Jun 2020, 15:02:41 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.