I agree that this site is using cookies. You can find further informations
here
.
X
Login
Merkliste (
0
)
Home
About us
Home About us
Our history
Profile
Press & public relations
Friends
The library in figures
Exhibitions
Projects
Training, internships, careers
Films
Services & Information
Home Services & Information
Lending and interlibrary loans
Returns and renewals
Training and library tours
My Account
Library cards
New to the library?
Download Information
Opening hours
Learning spaces
PC, WLAN, copy, scan and print
Catalogs and collections
Home Catalogs and Collections
Rare books and manuscripts
Digital collections
Subject Areas
Our sites
Home Our sites
Central Library
Law Library (Juridicum)
BB Business and Economics (BB11)
BB Physics and Electrical Engineering
TB Engineering and Social Sciences
TB Economics and Nautical Sciences
TB Music
TB Art & Design
TB Bremerhaven
Contact the library
Home Contact the library
Staff Directory
Open access & publishing
Home Open access & publishing
Reference management: Citavi & RefWorks
Publishing documents
Open Access in Bremen
zur Desktop-Version
Toggle navigation
Merkliste
1 Ergebnisse
1
Extreme Point Supervised Instance Segmentation:
, In:
2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
,
Lee, Hyeonjun
;
Hwang, Sehyun
;
Kwak, Suha
- p. 17212-17222 , 2024
Link:
https://doi.org/10.1109/CVPR52733.2024.01629
RT T1
2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
: T1
Extreme Point Supervised Instance Segmentation
UL https://suche.suub.uni-bremen.de/peid=ieee-10658352&Exemplar=1&LAN=DE A1 Lee, Hyeonjun A1 Hwang, Sehyun A1 Kwak, Suha YR 2024 SN 2575-7075 K1 Instance segmentation K1 Training K1 Computer vision K1 Costs K1 Annotations K1 Supervised learning K1 Benchmark testing K1 instance segmentation K1 label efficient learning K1 extreme point SP 17212 OP 17222 LK http://dx.doi.org/https://doi.org/10.1109/CVPR52733.2024.01629 DO https://doi.org/10.1109/CVPR52733.2024.01629 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)