Abstract: Systems, apparatuses, and methods for capturing voice messages are provided. In one embodiment, a method can include receiving, by one or more processors of a mobile user device, a user input indicative of a voice message at a first time. The method can further include identifying contextual data indicative of one or more computing devices within proximity of the mobile user device. The method can include providing a set of data for storage in one or more memory devices of the mobile user device. The set of data can indicate the voice message and the contextual data indicative of the computing devices. The method can further include providing an output indicative of the voice message and the contextual data to one or more secure computing devices at a second time.

Abstract: System and methods for a text summarization system are described. In one example, a text summarization system receives an input utterance and determines whether the utterance should be included in a summary of the text. The text summarization system includes an embedding network, a convolution network, an encoding component, and a summary component. The embedding network generates a semantic embedding of an utterance. The convolution network generates a plurality of feature vectors based on the semantic embedding. The encoding component identifies a plurality of latent codes respectively corresponding to the plurality of feature vectors. The summary component identifies a prominent code among the latent codes and to select the utterance as a summary utterance based on the prominent code.

Abstract: Embodiments of the present invention provide systems, methods, and computer storage media for identifying candidate boundaries for video segments, video segment selection using those boundaries, and text-based video editing of video segments selected via transcript interactions. In an example implementation, boundaries of detected sentences and words are extracted from a transcript, the boundaries are retimed into an adjacent speech gap to a location where voice or audio activity is a minimum, and the resulting boundaries are stored as candidate boundaries for video segments. As such, a transcript interface presents the transcript, interprets input selecting transcript text as an instruction to select a video segment with corresponding boundaries selected from the candidate boundaries, and interprets commands that are traditionally thought of as text-based operations (e.g., cut, copy, paste) as an instruction to perform a corresponding video editing operation using the selected video segment.

Abstract: Approaches are described for determining facial landmarks in images. An input image is provided to at least one trained neural network that determines a face region (e.g., bounding box of a face) of the input image and initial facial landmark locations corresponding to the face region. The initial facial landmark locations are provided to a 3D face mapper that maps the initial facial landmark locations to a 3D face model. A set of facial landmark locations are determined from the 3D face model. The set of facial landmark locations are provided to a landmark location adjuster that adjusts positions of the set of facial landmark locations based on the input image. The input image is presented on a user device using the adjusted set of facial landmark locations.

Abstract: A light-emitting system is provided which is removably attachable to headgear for personal illumination to enhance visibility of the user to others. The light-emitting system includes a housing that defines a receiving aperture and is configured to surround a portion of the headgear when the light-emitting system is removably attached to the headgear for use. The light-emitting system further includes at least one lens and a plurality of lighting elements coupled to the annular housing which are configured to selectively generate a halo or at least a partial halo of light that radiates outwardly away from the annular housing through the at least one lens to provide enhanced personal illumination.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that modify digital images via scene-based editing using image understanding facilitated by artificial intelligence. For instance, in one or more embodiments, the disclosed systems generate utilizing a segmentation neural network, an object mask for each object of a plurality of objects of a digital image. The disclosed systems detect a first user interaction with an object in the digital image displayed via a graphical user interface. The disclosed systems surface, via the graphical user interface, the object mask for the object in response to the first user interaction. The disclosed systems perform an object-aware modification of the digital image in response to a second user interaction with the object mask for the object.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that implement depth-aware object move operations for digital image editing. For instance, in some embodiments, the disclosed systems determine a first object depth for a first object portrayed within a digital image and a second object depth for a second object portrayed within the digital image. Additionally, the disclosed systems move the first object to create an overlap area between the first object and the second object within the digital image. Based on the first object depth and the second object depth, the disclosed systems modify the digital image to occlude the first object or the second object within the overlap area.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that modify digital images via multi-layered scene completion techniques facilitated by artificial intelligence. For instance, in some embodiments, the disclosed systems receive a digital image portraying a first object and a second object against a background, where the first object occludes a portion of the second object. Additionally, the disclosed systems pre-process the digital image to generate a first content fill for the portion of the second object occluded by the first object and a second content fill for a portion of the background occluded by the second object. After pre-processing, the disclosed systems detect one or more user interactions to move or delete the first object from the digital image. The disclosed systems further modify the digital image by moving or deleting the first object and exposing the first content fill for the portion of the second object.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that implement perspective-aware object move operations for digital image editing. For instance, in some embodiments, the disclosed systems determine a vanishing point associated with a digital image portraying an object. Additionally, the disclosed systems detect one or more user interactions for moving the object within the digital image. Based on moving the object with respect to the vanishing point, the disclosed systems perform a perspective-based resizing of the object within the digital image.

Abstract: Some embodiments involve a reinforcement learning based framework for training a natural media agent to learn a rendering policy without human supervision or labeled datasets. The reinforcement learning based framework feeds the natural media agent a training dataset to implicitly learn the rendering policy by exploring a canvas and minimizing a loss function. Once trained, the natural media agent can be applied to any reference image to generate a series (or sequence) of continuous-valued primitive graphic actions, e.g., sequence of painting strokes, that when rendered by a synthetic rendering environment on a canvas, reproduce an identical or transformed version of the reference image subject to limitations of an action space and the learned rendering policy.

Abstract: A light-emitting system is provided which is removably attachable to headgear for personal illumination to enhance visibility of the user to others. The light-emitting system includes a housing that defines a receiving aperture and is configured to surround a portion of the headgear when the light-emitting system is removably attached to the headgear for use. The light-emitting system further includes at least one lens and a plurality of lighting elements coupled to the annular housing which are configured to selectively generate a halo or at least a partial halo of light that radiates outwardly away from the annular housing through the at least one lens to provide enhanced personal illumination.

Abstract: Embodiments of the present invention provide an automated image tagging system that can predict a set of tags, along with relevance scores, that can be used for keyword-based image retrieval, image tag proposal, and image tag auto-completion based on user input. Initially, during training, a clustering technique is utilized to reduce cluster imbalance in the data that is input into a convolutional neural network (CNN) for training feature data. In embodiments, the clustering technique can also be utilized to compute data point similarity that can be utilized for tag propagation (to tag untagged images). During testing, a diversity based voting framework is utilized to overcome user tagging biases. In some embodiments, bigram re-weighting can down-weight a keyword that is likely to be part of a bigram based on a predicted tag set.

Abstract: Some embodiments involve a reinforcement learning based framework for training a natural media agent to learn a rendering policy without human supervision or labeled datasets. The reinforcement learning based framework feeds the natural media agent a training dataset to implicitly learn the rendering policy by exploring a canvas and minimizing a loss function. Once trained, the natural media agent can be applied to any reference image to generate a series (or sequence) of continuous-valued primitive graphic actions, e.g., sequence of painting strokes, that when rendered by a synthetic rendering environment on a canvas, reproduce an identical or transformed version of the reference image subject to limitations of an action space and the learned rendering policy.

Abstract: Embodiments of the present invention provide systems, methods, and non-transitory computer storage media for parsing a given input referring expression into a parse structure and generating a semantic computation graph to identify semantic relationships among and between objects. At a high level, when embodiments of the preset invention receive a referring expression, a parse tree is created and mapped into a hierarchical subject, predicate, object graph structure that labeled noun objects in the referring expression, the attributes of the labeled noun objects, and predicate relationships (e.g., verb actions or spatial propositions) between the labeled objects. Embodiments of the present invention then transform the subject, predicate, object graph structure into a semantic computation graph that may be recursively traversed and interpreted to determine how noun objects, their attributes and modifiers, and interrelationships are provided to downstream image editing, searching, or caption indexing tasks.

Abstract: Embodiments of the present invention provide systems, methods, and non-transitory computer storage media for parsing a given input referring expression into a parse structure and generating a semantic computation graph to identify semantic relationships among and between objects. At a high level, when embodiments of the preset invention receive a referring expression, a parse tree is created and mapped into a hierarchical subject, predicate, object graph structure that labeled noun objects in the referring expression, the attributes of the labeled noun objects, and predicate relationships (e.g., verb actions or spatial propositions) between the labeled objects. Embodiments of the present invention then transform the subject, predicate, object graph structure into a semantic computation graph that may be recursively traversed and interpreted to determine how noun objects, their attributes and modifiers, and interrelationships are provided to downstream image editing, searching, or caption indexing tasks.

Abstract: A light-emitting system is provided which is removably attachable to headgear for personal illumination to enhance visibility of the user to others. The light-emitting system includes a housing that defines a receiving aperture and is configured to surround a portion of the headgear when the light-emitting system is removably attached to the headgear for use. The light-emitting system further includes at least one lens and a plurality of lighting elements coupled to the annular housing which are configured to selectively generate a halo or at least a partial halo of light that radiates outwardly away from the annular housing through the at least one lens to provide enhanced personal illumination.

Abstract: System and methods for a text summarization system are described. In one example, a text summarization system receives an input utterance and determines whether the utterance should be included in a summary of the text. The text summarization system includes an embedding network, a convolution network, an encoding component, and a summary component. The embedding network generates a semantic embedding of an utterance. The convolution network generates a plurality of feature vectors based on the semantic embedding. The encoding component identifies a plurality of latent codes respectively corresponding to the plurality of feature vectors. The summary component identifies a prominent code among the latent codes and to select the utterance as a summary utterance based on the prominent code.

Abstract: Systems, apparatuses, and methods for capturing voice messages are provided. In one embodiment, a method can include receiving, by one or more processors of a mobile user device, a user input indicative of a voice message at a first time. The method can further include identifying contextual data indicative of one or more computing devices within proximity of the mobile user device. The method can include providing a set of data for storage in one or more memory devices of the mobile user device. The set of data can indicate the voice message and the contextual data indicative of the computing devices. The method can further include providing an output indicative of the voice message and the contextual data to one or more secure computing devices at a second time.

Abstract: A light-emitting system is provided which is removably attachable to headgear for personal illumination to enhance visibility of the user to others. The light-emitting system includes a housing that defines a receiving aperture and is configured to surround a portion of the headgear when the light-emitting system is removably attached to the headgear for use. The light-emitting system further includes at least one lens and a plurality of lighting elements coupled to the annular housing which are configured to selectively generate a halo or at least a partial halo of light that radiates outwardly away from the annular housing through the at least one lens to provide enhanced personal illumination.

Abstract: A suspension unit is provided which is removably coupleable to a helmet shell to enhance user safety and helmet functionality. The suspension unit includes: a suspension assembly configured to interface with a suspension attachment scheme of the helmet shell; one or more sensors carried by the suspension assembly and arranged to obtain biometric, environmental, location, motion, impact and/or other data; and a control system carried by the suspension assembly, the control system including at least a power source and a communication module, and being operatively coupled to the one or more sensors to obtain the biometric, environmental, location, motion, impact and/or other data and to transmit, via the communication module, a data signal to a computing device or network based at least in part on said data from which to enhance user safety and helmet functionality.