Abstract: Provided are systems and methods for portrait animation. An example method includes receiving, by a computing device, scenario data including information concerning movements of a first head, receiving, by the computing device, a target image including a second head and a background, determining, by the computing device and based on the target image and the information concerning the movements of the first head, two-dimensional (2D) deformations of the second head in the target image, applying, by the computing device, the 2D deformations to the target image to obtain at least one output frame of an output video, the at least one output frame including the second head displaced according to the movements of the first head, and filling, by the computing device and using a background prediction neural network, a portion of the background in gaps between the displaced second head and the background.

Abstract: Provided are systems and methods for portrait animation. An example method includes receiving, by a computing device, a scenario video, where the scenario video includes information concerning a first face, receiving, by the computing device, a target image, where the target image includes a second face, determining, by the computing device and based on the target image and the information concerning the first face, two-dimensional (2D) deformations of the second face in the target image, and applying, by the computing device, the 2D deformations to the target image to obtain at least one output frame of an output video.

Abstract: Provided are systems and methods for portrait animation. An example method includes receiving, by a computing device, a scenario video, where the scenario video includes information concerning a first face, receiving, by the computing device, a target image, where the target image includes a second face, determining, by the computing device and based on the target image and the information concerning the first face, two-dimensional (2D) deformations of the second face in the target image, and applying, by the computing device, the 2D deformations to the target image to obtain at least one output frame of an output video.

Abstract: Disclosed are systems and methods for portrait animation. An example method includes receiving, by a computing device, a scenario video, where the scenario video includes at least one input frame and the at least one input frame includes a first face, receiving, by the computing device, a target image, where the target image includes a second face, determining, by the computing device and based on the at least one input frame and the target image, two-dimensional (2D) deformations of the second face in the target image, where the 2D deformations, when applied to the second face, modify the second face to imitate at least a facial expression of the first face, and applying, by the computing device, the 2D deformations to the target image to obtain at least one output frame of an output video.

Abstract: Disclosed are systems and methods for portrait animation. An example method includes receiving, by a computing device, a scenario video, where the scenario video includes at least one input frame and the at least one input frame includes a first face, receiving, by the computing device, a target image, where the target image includes a second face, determining, by the computing device and based on the at least one input frame and the target image, two-dimensional (2D) deformations of the second face in the target image, where the 2D deformations, when applied to the second face, modify the second face to imitate at least a facial expression of the first face, and applying, by the computing device, the 2D deformations to the target image to obtain at least one output frame of an output video.

Abstract: Provided are systems and methods for photorealistic real-time portrait animation. An example method includes receiving a scenario video with at least one input frame. The input frame includes a first face of a first person. The method further includes receiving a target image with a second face of a second person. The method further includes determining, based on the at least one input frame and the target image, two-dimensional (2D) deformations of the second face and a background in the target image. The 2D deformations, when applied to the second face, modify the second face to imitate at least a facial expression and a head orientation of the first face. The method further includes applying the 2D deformations to the target image to obtain at least one output frame of an output video.

Abstract: Provided are systems and methods for photorealistic real-time portrait animation. An example method includes receiving a scenario video with at least one input frame. The input frame includes a first face of a first person. The method further includes receiving a target image with a second face of a second person. The method further includes determining, based on the at least one input frame and the target image, two-dimensional (2D) deformations of the second face and a background in the target image. The 2D deformations, when applied to the second face, modify the second face to imitate at least a facial expression and a head orientation of the first face. The method further includes applying the 2D deformations to the target image to obtain at least one output frame of an output video.

Abstract: Provided are systems and methods for photorealistic real-time portrait animation. An example method includes receiving a scenario video with at least one input frame. The input frame includes a first face. The method further includes receiving a target image with a second face. The method further includes determining, based on the at least one input frame and the target image, two-dimensional (2D) deformations, wherein the 2D deformations, when applied to the second face, modify the second face to imitate at least a facial expression and a head orientation of the first face. The method further includes applying, by the computing device, the 2D deformations to the target image to obtain at least one output frame of an output video.

Abstract: Provided are systems and methods for photorealistic real-time portrait animation. An example method includes receiving a scenario video with at least one input frame. The input frame includes a first face. The method further includes receiving a target image with a second face. The method further includes determining, based on the at least one input frame and the target image, two-dimensional (2D) deformations, wherein the 2D deformations, when applied to the second face, modify the second face to imitate at least a facial expression and a head orientation of the first face. The method further includes applying, by the computing device, the 2D deformations to the target image to obtain at least one output frame of an output video.

Abstract: Methods and systems for generating video previews are provided. In one embodiment, a method includes acquiring a video. The method allows extracting features of the video. The method further includes determining, based on the features, a genre of the video. The method can proceed with selecting, based on the features and the genre, a time fragment of the video. The method further includes cropping the time fragment to a rectangular shape to fit a screen of a mobile device positioned vertically. The method further includes compressing the cropped fragment into low bitrate video fragment.

Abstract: A web content enrichment system can match an image to text of web content. When the text of web content includes a snippet, the image matched to the text enriches the snippet to enhance results of a search engine. When the text of web content includes text contained in a webpage, the image matched to this text enriches the webpage to enhance user perception and understanding of the webpage. The process of matching images to text involves extracting features of a plurality of images and features of a plurality of text documents, calculating scores of the images based on the extracted features, and selecting one image per text document based on the scores using a machine-learning algorithm. The result of the matching can be provided to a web content module for storing, incorporating into the result lists of the search engine, or delivery to a user.