Abstract: Synthesizing high-resolution input for rendering a digital human includes generating, with a generative artificial intelligence (AI) model, a distorted image of the digital human by enhancing a region of interest (ROI) within the distorted image relative to other regions of the distorted image. The generative AI model is previously trained against a distorted control image generated using a distortion function to distort a control image used to guide image generation by the generative AI model. The distorted control image is generated by reconfiguring and augmenting pixels of the control image. An undistorted image of the digital human is generated using a reverse distortion function to reverse distortion of the distorted image.

Abstract: Computer-implemented content delivery includes caching a source content having a plurality of bridge points. A user event indicating an interaction with a user is received. The user event is received during playback of the source content. In response to the user event, a template is selected from a plurality of cached templates. The template corresponds to a bridge point selected from the plurality of bridge points of the source content as an exit point from the source content. In response to the user event, a bridge is dynamically generated. The bridge links the bridge point with the template. In response to the user event, a target content is selected from a plurality of cached target contents. In response to the user event, the bridge, the template, and the target content is conveyed to a device of the user for playback following the bridge point of the source content.