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First Order Motion Model for Image Animation

First Order Motion Model for Image AnimationAliaksandr SiarohinDISI, University of phane Lathuili reDISI, University of TrentoLTCI, T l com Paris, Institut polytechnique de TulyakovSnap RicciDISI, University of TrentoFondazione Bruno SebeDISI, University of TrentoHuawei Technologies Animation consists of generating a video sequence so that an object in asource Image is animated according to the Motion of a driving video. Our frame-work addresses this problem without using any annotation or prior informationabout the specific object to animate. Once trained on a set of videos depictingobjects of the same category ( , human bodies), our method can be appliedto any object of this class. To achieve this, we decouple appearance and motioninformation using a self-supervised formulation.

recurrent neural network with a VAE in order to generate face videos. Considering a wider range of applications, Tulyakov et al. [34] introduced MoCoGAN, a recurrent architecture adversarially trained in order to synthesize videos from noise, categorical labels or …

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