Abstract: The present invention sets forth a technique for performing virtual object placement in a video sequence. The technique includes identifying a planar surface depicted in an input video sequence and selecting a virtual object included in an object library. The technique also includes generating, for a combination of the planar surface and the virtual object, a suitability metric associated with the combination, wherein the suitability metric is based at least on a semantic compatibility between the virtual object and the planar surface. The technique further includes generating, via one or more machine learning models, a modified video sequence based on the suitability metric, where the modified video sequence depicts the virtual object placed on the planar surface.

Abstract: One embodiment of the present invention sets forth a technique for performing estimation of scene parameters associated with a two-dimensional (2D) input scene. technique includes identifying, based on the input scene, one or more line segments included in the input scene and generating one or more vanishing points associated with the input scene based on the one or more line segments. The technique also includes estimating, based on the one or more vanishing points, one or more scene parameters associated with the scene and inserting a world object into the input scene based on the one or more scene parameters.

Abstract: One embodiment of the present invention sets forth a technique for estimating a real-world size of an object included in an input scene. The technique includes identifying one or more depictions of human faces included in a two-dimensional input scene and generating one or more bounding boxes associated with the input scene, where each bounding box represents a head size associated with a different one of the one or more depictions of human faces. The technique also includes calculating a relative depth value for each of one or more pixels included in the input scene. The technique further includes calculating an average relative head size based on the one or more bounding boxes and relative depth values associated with the one or more pixels and generating a depth scale based on the average relative head size and a known real-world dimension of an average human head.

Abstract: Systems, devices, and methods are provided for depth-guided structure from motion. A system may obtain a plurality of image frames from a digital content item that corresponds to a scene and determine, based at least in part on a correspondence search, a set of 2-D keypoints for the plurality of image frames. A depth estimator may be used to determine a plurality of dense depth map for the plurality of image frames. The set of 2-D keypoints and the plurality of dense depth maps may be used to determine a corresponding set of depth priors. Initialization and/or depth-regularized optimization may be performed using the keypoints and depth priors.

Abstract: Techniques are disclosed for detecting an uncovered portion of a body of a person in a frame of video content. In an example, a first machine learning model of a computing system may output a first score for the frame based on a map that identifies a region of the frame associated with an uncovered body part type. Depending on a value of the first score, a second machine learning model that includes a neural network architecture may further analyze the frame to output a second score. The first score and second score may be merged to produce a third score for the frame. A plurality of scores may be determined, respectively, for frames of the video content, and a maximum score may be selected. The video content may be selected for presentation on a display for further evaluation based on the maximum score.

Abstract: A system can be utilized to retrieve media content and rating schemas, to determine maturity ratings for media content. The media content can be utilized to determine segments of data as building blocks associated with mature content. The building blocks can be mapped to content descriptors and rating levels associated with the rating schemas. The building blocks can be compared the media content to identify portions of the media content that have characteristics represented by the building blocks. The building blocks representing the characteristics in the portions of the media content can be utilized to select content descriptors and rating levels associated with the media content. The selected content descriptor and selected rating levels can be utilized to control how, and/or whether, the media content is made available for output to the consumers.

Abstract: Systems, devices, and methods are provided for depth guided structure from motion. A system may obtain a plurality of image frames from a digital content item that corresponds to a scene and determine, based at least in part on a correspondence search, a set of 2-D keypoints for the plurality of image frames. A depth estimator may be used to determine a plurality of dense depth map for the plurality of image frames. The set of 2-D keypoints and the plurality of dense depth maps may be used to determine a corresponding set of depth priors. Initialization and/or depth-regularized optimization may be performed using the keypoints and depth priors.

Abstract: Techniques for a computer-implemented service for virtual product placement in video frames are described. According to some embodiments, a computer-implemented method includes receiving, at a virtual product placement service, a request to place a two-dimensional image of a virtual product into a video, identifying, by a machine learning model of the virtual product placement service, a surface depicted in the video for insertion of the two-dimensional image of the virtual product, inserting, by the virtual product placement service, of the two-dimensional image of the virtual product into one or more frames of the video onto the surface to generate a video including the virtual product, and transmitting the video including the virtual product to a viewer device or a storage location.

Abstract: Disclosed are various embodiments for seamless insertion of modified media content. In one embodiment, a modified portion of video content is received. The modified portion has a start cue point and an end cue point that are set relative to a modification to the video content to indicate respectively when the modification approximately begins and ends compared to the video content. A video coding associated with the video content is identified. The start cue point and/or the end cue point are dynamically adjusted to align the modified portion with the video content based at least in part on the video coding.

Abstract: Techniques are disclosed for detecting an uncovered portion of a body of a person in a frame of video content. In an example, a first machine learning model of a computing system may output a first score for the frame based on a map that identifies a region of the frame associated with an uncovered body part type. Depending on a value of the first score, a second machine learning model that includes a neural network architecture may further analyze the frame to output a second score. The first score and second score may be merged to produce a third score for the frame. A plurality of scores may be determined, respectively, for frames of the video content, and a maximum score may be selected. The video content may be selected for presentation on a display for further evaluation based on the maximum score.

Abstract: Techniques are described for automating virtual placements in video content.

Abstract: Techniques are disclosed for detecting a type of prurient activity shown by a portion of video content. In an example, a machine learning model of a computer system may receive a second portion of video content, the machine learning model including a neural network that is trained to analyze a temporal dimension of the second portion. The machine learning model determines a score indicating a likelihood that the video content shows the type of prurient activity based in part on applying a three-dimensional filter to the second portion of the video content. The computer system then generates a video clip that includes at least the portion of the video content showing the type of prurient activity based on the score, and provides the video clip for display.

Abstract: Techniques are described for automating virtual placements in video content.

Abstract: Systems and methods for security in power systems are provided. A security-aware distributed control framework for resilient operation of power systems can detect and mitigate different types of attacks that might target power systems. The framework can discover a change in the features of transmitted data from neighbor agents, discard an infected agent, and achieve an updated consensus protocol agreement while satisfying a control system objective.

Abstract: This disclosure describes techniques that relate generally to the collection, processing, storage, and graphical representation of medical imaging data associated with patient care. Medical imaging data may be processed using object recognition algorithms to help determined pertinent medical characteristics. Further, a graphical fusion application may generate a graphical representation of medical data that is based at least in part on a combination of medical imaging data and corresponding interpretation data. The graphical representation may overlay a schematic diagram of a relevant organ system, so as to provide a medical practitioner with a visual, more specifically graphical, indication of the medical imaging data. Interpretation data of pertinent medical characteristics may be generated by an automated analysis of the medical imaging data.

Abstract: Techniques are described for analyzing patient image data relative to stored medical image data. A Registry & Image Data Analytics (RIDA) system is described that is configured to analyze medical image data, generate corresponding metadata, and selectively store the medical image data, and metadata, within a registry & image data repository. The RIDA system may be configured to extract pertinent medical data from medical image data that is related to patient care, medical examinations and/or medical research. In doing so, the RIDA system may infer a medical diagnosis based on an analysis of patient image data. Additionally, the RIDA system may infer the validity of a medical hypothesis based at least in part on an analysis of patient image data. The RIDA system may also generate and store a synthesized expression of a text-based or audio-based user input into patient image data and/or corresponding registry data record.