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
Bending Reality: Distortion-aware Transformers for Adapting..:
, In:
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
,
Zhang, Jiaming
;
Yang, Kailun
;
Ma, Chaoxiang
... - p. 16896-16906 , 2022
Link:
https://doi.org/10.1109/CVPR52688.2022.01641
RT T1 <cTitle>2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)</cTitle>: T1 <Title>Bending Reality: Distortion-aware Transformers for Adapting to Panoramic Semantic Segmentation</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-9879838&Exemplar=1&LAN=DE A1 Zhang, Jiaming A1 Yang, Kailun A1 Ma, Chaoxiang A1 Reiss, Simon A1 Peng, Kunyu A1 Stiefelhagen, Rainer YR 2022 SN 2575-7075 K1 Training K1 Image segmentation K1 Adaptation models K1 Annotations K1 Shape K1 Semantics K1 Transformers K1 Scene analysis and understanding; Segmentation K1 grouping and shape analysis; Self-& semi-& meta- & unsupervised learning SP 16896 OP 16906 LK http://dx.doi.org/https://doi.org/10.1109/CVPR52688.2022.01641 DO https://doi.org/10.1109/CVPR52688.2022.01641 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)
