Abstract: Systems, methods, and computer-readable media are disclosed for systems and methods for automated generation and presentation of sign language avatars for video content. Example methods may include determining, by one or more computer processors coupled to memory, a first segment of video content, the first segment including a first set of frames, first audio content, and first subtitle data, where the first subtitle data comprises a first word and a second word. Methods may include determining, using a first machine learning model, a first sign gesture associated with the first word, determining first motion data associated with the first sign gesture, and determining first facial expression data. Methods may include generating an avatar configured to perform the first sign gesture using the first motion data, where a facial expression of the avatar while performing the first sign gesture is based on the first facial expression data.

Abstract: A method for identifying a hand pose in a vehicle involves identifying a hand image for a hand in the vehicle by extraction from a vehicle image of the vehicle. A plurality of contextual images of the hand image is obtained based on the single point. Each of the plurality of contextual images are processed using one or more layers of a neural network to obtain a plurality of contextual features associated with the hand image. A hand pose associated with the hand is identified based on the plurality of contextual features using a classifier model.

Abstract: A method for identifying a hand pose in a vehicle involves identifying a hand image for a hand in the vehicle by extraction from a vehicle image of the vehicle. A plurality of contextual images of the hand image is obtained based on the single point. Each of the plurality of contextual images are processed using one or more layers of a neural network to obtain a plurality of contextual features associated with the hand image. A hand pose associated with the hand is identified based on the plurality of contextual features using a classifier model.

Abstract: Fusion polypeptides capable of binding endothelin-1 to form a non-functional complex are provided, including amino acid sequences of the fusion polypeptides. The fusion polypeptides will be linked to the Fe portion of human IgG I to form dimers that will function as endothelin-1 antagonists (endothelin-1 sponge).

Abstract: Fusion polypeptides capable of binding endothelin-1 to form a non-functional complex are provided, including amino acid sequences of the fusion polypeptides. The fusion polypeptides will be linked to the Fe portion of human IgG I to form dimers that will function as endothelin-1 antagonists (endothelin-1 sponge).

Abstract: The invention concerns a computer-implemented method for tracking and reshaping a human-shaped figure in a digital video comprising the steps: acquiring a body model of the figure from the digital video, adapting a shape of the body model, modifying frames of the digital video, based on the adapted body model and outputting the digital video.

Abstract: The invention concerns a computer-implemented method for tracking and reshaping a human-shaped figure in a digital video comprising the steps: acquiring a body model of the figure from the digital video, adapting a shape of the body model, modifying frames of the digital video, based on the adapted body model and outputting the digital video.