Zobrazeno 1 - 10
of 28
pro vyhledávání: '"Ira Kemelmacher-Shlizerman"'
Publikováno v:
ACM Transactions on Graphics. 40:1-10
Given a pair of images---target person and garment on another person---we automatically generate the target person in the given garment. Previous methods mostly focused on texture transfer via paired data training, while overlooking body shape deform
Every time you sit in front of a TV or monitor, your face is actively illuminated by time-varying patterns of light. This paper proposes to use this time-varying illumination for synthetic relighting of your face with any new illumination condition.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f9d800e736b02a7dc4966086aa8a9182
Autor:
Ira Kemelmacher-Shlizerman, Laura Trutoiu, Joelle Zimmermann, John F. Akers, Brian T. Schowengerdt
Publikováno v:
SUI
We present a case study on the use of mixed reality (MR) spatial computing in a fully remote classroom. We conducted a 10-week undergraduate class fully online, using a combination of traditional teleconferencing software and MR spatial computing (Ma
Autor:
Soumyadip Sengupta, Steven M. Seitz, Ira Kemelmacher-Shlizerman, Vivek Jayaram, Brian Curless
Publikováno v:
CVPR
We propose a method for creating a matte -- the per-pixel foreground color and alpha -- of a person by taking photos or videos in an everyday setting with a handheld camera. Most existing matting methods require a green screen background or a manuall
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c67f09721092c3a80006e5d88d836c15
Autor:
Steve Seitz, Andrey Ryabtsev, Soumyadip Sengupta, Shanchuan Lin, Brian Curless, Ira Kemelmacher-Shlizerman
Publikováno v:
CVPR
We introduce a real-time, high-resolution background replacement technique which operates at 30fps in 4K resolution, and 60fps for HD on a modern GPU. Our technique is based on background matting, where an additional frame of the background is captur
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6017129ee1a46a46a87ada0396cf804d
Publikováno v:
Computer Vision – ECCV 2020 ISBN: 9783030585389
ECCV (6)
ECCV (6)
We address the problem of single photo age progression and regression—the prediction of how a person might look in the future, or how they looked in the past. Most existing aging methods are limited to changing the texture, overlooking transformati
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d9bd9581cb27cdfec44b905f53910ec7
https://doi.org/10.1007/978-3-030-58539-6_44
https://doi.org/10.1007/978-3-030-58539-6_44
Publikováno v:
ACM Transactions on Graphics. 36:1-13
Given audio of President Barack Obama, we synthesize a high quality video of him speaking with accurate lip sync, composited into a target video clip. Trained on many hours of his weekly address footage, a recurrent neural network learns the mapping
Publikováno v:
CVPR
We present a method and application for animating a human subject from a single photo. E.g., the character can walk out, run, sit, or jump in 3D. The key contributions of this paper are: 1) an application of viewing and animating humans in single pho
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::10d404e7d9c8755274e6ea8de7f8e592
http://arxiv.org/abs/1812.02246
http://arxiv.org/abs/1812.02246
Autor:
Ira Kemelmacher-Shlizerman
Publikováno v:
ACM Transactions on Graphics. 35:1-8
People may look dramatically different by changing their hair color, hair style, when they grow older, in a different era style, or a different country or occupation. Some of those may transfigure appearance and inspire creative changes, some not, bu
Publikováno v:
CVPR
We present a system that transforms a monocular video of a soccer game into a moving 3D reconstruction, in which the players and field can be rendered interactively with a 3D viewer or through an Augmented Reality device. At the heart of our paper is
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::53c8533e7acdb66b17f6e90740581f42