Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Hirner, Dominik"'
Stereo estimation has made many advancements in recent years with the introduction of deep-learning. However the traditional supervised approach to deep-learning requires the creation of accurate and plentiful ground-truth data, which is expensive to
Externí odkaz:
http://arxiv.org/abs/2410.13500
We propose an accurate and lightweight convolutional neural network for stereo estimation with depth completion. We name this method fully-convolutional deformable similarity network with depth completion (FCDSN-DC). This method extends FC-DCNN by im
Externí odkaz:
http://arxiv.org/abs/2209.06525
We propose a novel lightweight network for stereo estimation. Our network consists of a fully-convolutional densely connected neural network (FC-DCNN) that computes matching costs between rectified image pairs. Our FC-DCNN method learns expressive fe
Externí odkaz:
http://arxiv.org/abs/2010.06950
Proceedings of the OAGM & ARW Joint Workshop Vision, Automation and Robotics
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6bdb6c6bd9177782add870d0f98cb78a