Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Ibrahimli, Nail"'
We introduce MuVieCAST, a modular multi-view consistent style transfer network architecture that enables consistent style transfer between multiple viewpoints of the same scene. This network architecture supports both sparse and dense views, making i
Externí odkaz:
http://arxiv.org/abs/2312.05046
Feedforward fully convolutional neural networks currently dominate in semantic segmentation of 3D point clouds. Despite their great success, they suffer from the loss of local information at low-level layers, posing significant challenges to accurate
Externí odkaz:
http://arxiv.org/abs/2212.12402
Traditional MVS methods have good accuracy but struggle with completeness, while recently developed learning-based multi-view stereo (MVS) techniques have improved completeness except accuracy being compromised. We propose depth discontinuity learnin
Externí odkaz:
http://arxiv.org/abs/2203.01391
Autor:
Turan, Mehmet, Ornek, Evin Pinar, Ibrahimli, Nail, Giracoglu, Can, Almalioglu, Yasin, Yanik, Mehmet Fatih, Sitti, Metin
In the last decade, many medical companies and research groups have tried to convert passive capsule endoscopes as an emerging and minimally invasive diagnostic technology into actively steerable endoscopic capsule robots which will provide more intu
Externí odkaz:
http://arxiv.org/abs/1803.01047
Autor:
Ibrahimli, Nail1 (AUTHOR) liangliang.nan@tudelft.nl, Ledoux, Hugo1 (AUTHOR), Kooij, Julian F. P.2 (AUTHOR), Nan, Liangliang1 (AUTHOR)
Publikováno v:
Remote Sensing. Jun2023, Vol. 15 Issue 12, p2970. 18p.
