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
A Cross Branch Fusion-Based Contrastive Learning Framework ..:
, In:
2024 International Conference on 3D Vision (3DV)
,
Wu, Chengzhi
;
Huang, Qianliang
;
Jin, Kun
.. - p. 528-538 , 2024
Link:
https://doi.org/10.1109/3DV62453.2024.00012
RT T1
2024 International Conference on 3D Vision (3DV)
: T1
A Cross Branch Fusion-Based Contrastive Learning Framework for Point Cloud Self-supervised Learning
UL https://suche.suub.uni-bremen.de/peid=ieee-10550674&Exemplar=1&LAN=DE A1 Wu, Chengzhi A1 Huang, Qianliang A1 Jin, Kun A1 Pfrommer, Julius A1 Beyerer, Jurgen YR 2024 SN 2475-7888 K1 Point cloud compression K1 Representation learning K1 Three-dimensional displays K1 Training data K1 Benchmark testing K1 Data models K1 Task analysis SP 528 OP 538 LK http://dx.doi.org/https://doi.org/10.1109/3DV62453.2024.00012 DO https://doi.org/10.1109/3DV62453.2024.00012 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)