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18.11.2017, 09:02
Wenn man dieses Video sieht, fragt man sich, was von dem, was uns im TV gezeigt wird, überhaupt noch der Realität entsprich?!
Face2Face: Real-time Face Capture and Reenactment of RGB Videos (CVPR 2016 Oral)
https://www.youtube.com/watch?time_continue=2&v=ohmajJTcpNk
oder noch besser dieses hier:
https://www.youtube.com/watch?v=ttGUiwfTYvg
ABONNIEREN 50.000
A research team has created software that allows them to control the face of anyone in any video on YouTube. The result is a weird cross between Snapchat’s “face swap” feature and the “gibberish” scene from Bruce Almighty.Here's the original study: http://www.graphics.stanford.edu/~nie... (https://www.youtube.com/redirect?redir_token=m2ABlQpeV1b1BFau-EBNquiyfvB8MTUxMTA4MTQyOEAxNTEwOTk1MDI4&v=ttGUiwfTYvg&q=http%3A%2F%2Fwww.graphics.stanford.edu%2F%7Enies sner%2Fthies2016face.html&event=video_description)
Wird uns vielleicht eines Tages Putins Kriegserklärung im TV vorgespielt, entstanden in einem Studio, damit wir verstehen, warum die USA die Russen militärisch angreifen?
We present the first real-time high-fidelity facial capture method. The core idea is to enhance a global real-time face tracker, which provides a low-resolution face mesh, with local regressors that add in medium-scale details, such as expression wrinkles. Our main observation is that although wrinkles appear in different scales and at different locations on the face, they are locally very self-similar and their visual appearance is a direct consequence of their local shape. We therefore train local regressors from high-resolution capture data in order to predict the local geometry from local appearance at runtime. We propose an automatic way to detect and align the local patches required to train the regressors and run them efficiently in real-time. Our formulation is particularly designed to enhance the low-resolution global tracker with exactly the missing expression frequencies, avoiding superimposing spatial frequencies in the result. Our system is generic and can be applied to any real-time tracker that uses a global prior, e.g. blend-shapes. Once trained, our online capture approach can be applied to any new user without additional training, resulting in high-fidelity facial performance reconstruction with person-specific wrinkle details from a monocular video camera in real-time.
https://www.youtube.com/watch?v=MMa2oT1wMIs
Sicher ist euch schon lange aufgefallen, dass im www oder in Photo-Bearbeitungsprogrammen immer mehr Wert auf Gesichtserkennung gelegt wird, und man auch aufgefordert wird, die gezeigten Gesichter mit Namen zu nennen. Ein Schelm...
Face2Face: Real-time Face Capture and Reenactment of RGB Videos (CVPR 2016 Oral)
https://www.youtube.com/watch?time_continue=2&v=ohmajJTcpNk
oder noch besser dieses hier:
https://www.youtube.com/watch?v=ttGUiwfTYvg
ABONNIEREN 50.000
A research team has created software that allows them to control the face of anyone in any video on YouTube. The result is a weird cross between Snapchat’s “face swap” feature and the “gibberish” scene from Bruce Almighty.Here's the original study: http://www.graphics.stanford.edu/~nie... (https://www.youtube.com/redirect?redir_token=m2ABlQpeV1b1BFau-EBNquiyfvB8MTUxMTA4MTQyOEAxNTEwOTk1MDI4&v=ttGUiwfTYvg&q=http%3A%2F%2Fwww.graphics.stanford.edu%2F%7Enies sner%2Fthies2016face.html&event=video_description)
Wird uns vielleicht eines Tages Putins Kriegserklärung im TV vorgespielt, entstanden in einem Studio, damit wir verstehen, warum die USA die Russen militärisch angreifen?
We present the first real-time high-fidelity facial capture method. The core idea is to enhance a global real-time face tracker, which provides a low-resolution face mesh, with local regressors that add in medium-scale details, such as expression wrinkles. Our main observation is that although wrinkles appear in different scales and at different locations on the face, they are locally very self-similar and their visual appearance is a direct consequence of their local shape. We therefore train local regressors from high-resolution capture data in order to predict the local geometry from local appearance at runtime. We propose an automatic way to detect and align the local patches required to train the regressors and run them efficiently in real-time. Our formulation is particularly designed to enhance the low-resolution global tracker with exactly the missing expression frequencies, avoiding superimposing spatial frequencies in the result. Our system is generic and can be applied to any real-time tracker that uses a global prior, e.g. blend-shapes. Once trained, our online capture approach can be applied to any new user without additional training, resulting in high-fidelity facial performance reconstruction with person-specific wrinkle details from a monocular video camera in real-time.
https://www.youtube.com/watch?v=MMa2oT1wMIs
Sicher ist euch schon lange aufgefallen, dass im www oder in Photo-Bearbeitungsprogrammen immer mehr Wert auf Gesichtserkennung gelegt wird, und man auch aufgefordert wird, die gezeigten Gesichter mit Namen zu nennen. Ein Schelm...