English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
 
 
DownloadE-Mail
  Lucid Data Dreaming for Video Object Segmentation

Khoreva, A., Benenson, R., Ilg, E., Brox, T., & Schiele, B. (2019). Lucid Data Dreaming for Video Object Segmentation. International Journal of Computer Vision, 127(9), 1175-1197. doi:10.1007/s11263-019-01164-6.

Item is

Files

show Files
hide Files
:
Khoreva2019_Article_LucidDataDreamingForVideoObjec.pdf (Publisher version), 17MB
Name:
Khoreva2019_Article_LucidDataDreamingForVideoObjec.pdf
Description:
-
OA-Status:
Visibility:
Public
MIME-Type / Checksum:
application/pdf / [MD5]
Technical Metadata:
Copyright Date:
-
Copyright Info:
Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made

Locators

show

Creators

show
hide
 Creators:
Khoreva, Anna1, Author           
Benenson, Rodrigo2, Author           
Ilg, Eddy2, Author
Brox, Thomas2, Author
Schiele, Bernt1, Author           
Affiliations:
1Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society, ou_1116547              
2External Organizations, ou_persistent22              

Content

show

Details

show
hide
Language(s): eng - English
 Dates: 20192019
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: Khoreva2019
DOI: 10.1007/s11263-019-01164-6
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: International Journal of Computer Vision
  Other : Int. J. Comput. Vis.
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: New York, NY : Springer
Pages: - Volume / Issue: 127 (9) Sequence Number: - Start / End Page: 1175 - 1197 Identifier: ISSN: 0920-5691
CoNE: https://pure.mpg.de/cone/journals/resource/954925564668