Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Stanislav Pidhorskyi"'
Autor:
Stanislav Pidhorskyi, Timur Bagautdinov, Shugao Ma, Jason Saragih, Gabriel Schwartz, Yaser Sheikh, Tomas Simon
Publikováno v:
ACM Transactions on Graphics. 41:1-18
Cameras with a finite aperture diameter exhibit defocus for scene elements that are not at the focus distance, and have only a limited depth of field within which objects appear acceptably sharp. In this work we address the problem of applying invers
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bc92a43bf471ea6a2d562a9c64b01f72
https://doi.org/10.1145/3550454.3555521
https://doi.org/10.1145/3550454.3555521
Autor:
Melanie Clemmer, Neel Rao, Treah Haggerty, Hannah Staggs, Donald A. Adjeroh, Melissa D. Olfert, Kelsey Kinnamon, D. Leann Long, Stanislav Pidhorskyi, Peter R. Giacobbi, Danielle Symons Downs, Shari A. Steinman
Publikováno v:
J Midwifery Womens Health
Introduction Pregnancy presents health challenges related to well-being, physical activity, dietary regulation, and body image. There is evidence to support the use of guided imagery to address these concerns during pregnancy. The purpose of this stu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::53931f053274203e2aaa9f5b129f7985
https://doi.org/10.1111/jmwh.13251
https://doi.org/10.1111/jmwh.13251
Publikováno v:
CVPR
Autoencoder networks are unsupervised approaches aiming at combining generative and representational properties by learning simultaneously an encoder-generator map. Although studied extensively, the issues of whether they have the same generative pow
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::36852b16bfb7b6bff4a4efc85469516b
https://doi.org/10.1109/cvpr42600.2020.01411
https://doi.org/10.1109/cvpr42600.2020.01411
Publikováno v:
Computer Vision – ACCV 2018 ISBN: 9783030208691
ACCV (4)
ACCV (4)
Deep hashing approaches are widely applied to approximate nearest neighbor search for large-scale image retrieval. We propose Spherical Deep Supervised Hashing (SDSH), a new supervised deep hashing approach to learn compact binary codes. The goal of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4294fb82bf5032a2619dd6614d66bea0
https://doi.org/10.1007/978-3-030-20870-7_26
https://doi.org/10.1007/978-3-030-20870-7_26
