Adobe

Abstract In one aspect, a processor determines a first set of video frames of a video based on a target video frame. The first set of video frames includes the target video frame, one or more frames of the video preceding the target video frame, and one or more frames of the video subsequent to the target video frame. The first set of video frames includes a sequence of video frames of the video. An encoder neural network executing on the processor encodes the first set of video frames of a video to generate a respective feature vector for each video frame in the first set. A decoder neural network executing on the processor decodes the feature vectors to generate a mask for the target video frame.

Abstract A feedback management subsystem receives, from a first user, first text comprising commentary on an item. The feedback management subsystem receives, from the first user, instructions to request commentary on the item from a second user. Responsive to receiving the instructions to request commentary from the second user, a communication subsystem transmits a notification to the second user. The feedback management subsystem receives, from the second user, second text comprising commentary on the item. A first machine learning model performs sentiment analysis to identify sentiments of the first text and the second text. A recommendation subsystem identifies prior actions of the first user and associated sentiments of the second user. A second machine learning model identifies a second item based on the prior actions of the first user and the sentiments of the second user. The recommendation subsystem provides output to the first user recommending the second item.

Abstract An image generation system accessing an input image displayed on a user interface. The image generation system receives, via the user interface, a target style text defining a target style for a stylized image to be generated based on the input image and a request to generate the stylized image. The image generation system generates the stylized image. Generating the stylized image includes applying a text guided image generation model to the input image and the target style text, wherein the text guided image generation model minimizes a loss between a first relationship between the generated stylized image and a set of style templates and a second relationship between the target style text and the set of style templates. The image generation system displays, via the user interface responsive to receiving the request, the generated stylized image.

Abstract Systems and methods include generating synthetic videos based on a custom motion. A video generation system obtains a text prompt including an object and a custom motion token. The custom motion token represents a custom motion. The system encodes the text prompt to obtain a text embedding. Subsequently, a video generation model generates a synthetic video depicting the object performing the custom motion based on the text embedding using a video generation model.

Abstract Dialogue state aware dialogue summarization techniques are described that enable generation of dialogue summaries from target domains with limited training data. A content processing system, for instance, generates one or more clusters based on training dialogues from one or more source domains. The clusters represent domain-specific features of the training dialogues and are further based on dialogue states of the training dialogues. The content processing system trains a machine learning model to generate summaries of dialogues by using the one or more clusters as prefixes in a prefix-tuning approach. The content processing system receives an input that includes a dialogue from a target domain. The content processing system generates an input prompt based on the dialogue and the one or more clusters, and the model generates a summary of the dialogue based on the input prompt.

Abstract A method, apparatus, non-transitory computer readable medium, and system for video summarization include obtaining a video, generating a sequence of contextualized visual representations corresponding to portions of the video, generating a sequence of summary visual representations corresponding to a subset of the portions of the video based on the sequence of contextualized visual representations, and generating a summary video including the subset of the portions of the video based on the sequence of summary visual representations.

Abstract The disclosed systems, methods, and non-transitory computer readable media provide a digital design interface for creating and modifying circular arc segments as drawing elements within an arc path segment in a cohesive and visually consistent manner. In particular, the disclosed systems generate a circular arc segment comprising a first endnode and a second endnode, wherein the second endnode of the circular arc segment is connected to a design segment comprising the second endnode and a third endnode. In addition, the disclosed systems determine a first continuity setting for the first endnode, a second continuity setting for the second endnode, and a third continuity setting for the third endnode. Moreover, in response to a user interaction, the disclosed systems generate a modified circular arc segment and a modified design segment according to the first continuity setting, the second continuity setting, and the third continuity setting.

Abstract Embodiments are disclosed for a process of detecting and processing curved text in a document using a digital design system. The method may include identifying, by a page segmentation model, a plurality of paragraph objects in a document. The disclosed systems and methods further comprise determining that a paragraph object of the plurality of paragraph objects includes curved text in view of positions of baselines of text runs in the paragraph object. The processing of the curved text in the paragraph object can include determining spacing data for text runs of the curved text in the paragraph object. The disclosed systems and methods further comprise presenting output data representing the curved text using the spacing data for the text runs of the curved text.