Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Rinon Gal"'
Publikováno v:
Special Interest Group on Computer Graphics and Interactive Techniques Conference Proceedings.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a911ada8ed118b84c4a7da9b3ae77c89
https://doi.org/10.1145/3528233.3530698
https://doi.org/10.1145/3528233.3530698
The ability of Generative Adversarial Networks to encode rich semantics within their latent space has been widely adopted for facial image editing. However, replicating their success with videos has proven challenging. Sets of high-quality facial vid
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8361b1ee768b23fdad79f3dfd8597170
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031200434
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::02dc44bcc52b42d0981ef7f4bb7fd599
https://doi.org/10.1007/978-3-031-20044-1_32
https://doi.org/10.1007/978-3-031-20044-1_32
Publikováno v:
2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f4993f286ace9a625e4f0dc50e88fe91
https://doi.org/10.1109/iccvw54120.2021.00231
https://doi.org/10.1109/iccvw54120.2021.00231
In recent years, considerable progress has been made in the visual quality of Generative Adversarial Networks (GANs). Even so, these networks still suffer from degradation in quality for high-frequency content, stemming from a spectrally biased archi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::666fa4e4c7aa5b7066e68b0260b027b3
http://arxiv.org/abs/2102.06108
http://arxiv.org/abs/2102.06108
Publikováno v:
DocEng
Graph Convolutional Networks (GCN) have been recognized as successful for processing pseudo-spatial graph representations of the underlying structure of documents. We present Cardinal Graph Convolutional Networks (CGCN), an efficient and flexible ext
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d5e0cbc686b31b70a3f51e851472d1ed
https://doi.org/10.1145/3395027.3419584
https://doi.org/10.1145/3395027.3419584
Publikováno v:
Computer Vision – ACCV 2018 ISBN: 9783030208899
ACCV (2)
ACCV (2)
Receipts are crucial for many businesses’ operation, where expenses are tracked meticulously. Receipt documents are often scanned into images, digitized and analyzed before the information is streamed into institutional financial applications. The
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b1ea0de0302655da611f450f04d22a5d
https://doi.org/10.1007/978-3-030-20890-5_35
https://doi.org/10.1007/978-3-030-20890-5_35