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We are given a video of a person performing a certain activity, from which weextract a controllable model. The model generates novel image sequences of thatperson, according to arbitrary user-defined control signals, typically markingthe displacement of the moving body. The generated video can have an arbitrarybackground, and effectively capture both the dynamics and appearance of theperson.  The method is based on two networks. The first network maps a current pose,and a single-instance control signal to the next pose. The second network mapsthe current pose, the new pose, and a given background, to an output frame.Both networks include multiple novelties that enable high-quality performance.This is demonstrated on multiple characters extracted from various videos ofdancers and athletes.

Vid2Game: Controllable Characters Extracted from Real-World Videos