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• W3120490802 abstract "This work represents a simple method for motion transfer (i.e., given a source video of a subject [person] performing some movements or in motion, that movement/motion is transferred to amateur target in different motion). The pose is used as an intermediate representation to perform this translation. To transfer the motion of the source subject to the target subject, the pose is extracted from the source subject, and then the target subject is generated by applying the learned pose to-appearance mapping. To perform this translation, the video is considered as a set of images consisting of all the frames. Generative adversarial networks (GANs) are used to transfer the motion from source subject to the target subject. GANs are an evolving field of deep learning." @default.
• W3120490802 created "2021-01-18" @default.
• W3120490802 creator A5056385668 @default.
• W3120490802 date "2021-01-01" @default.
• W3120490802 modified "2023-09-23" @default.
• W3120490802 title "Motion Imitation for Monocular Videos" @default.
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• W3120490802 doi "https://doi.org/10.4018/978-1-7998-7511-6.ch008" @default.
• W3120490802 hasPublicationYear "2021" @default.
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