Abstract: According to one implementation, a system for redirecting to content after an interruption includes a computing platform having a hardware processor and a system memory storing a content redirection software code. The hardware processor executes the content redirection software code to track a playout status of a primary content being provided by the system, and detect a pause to playout of the primary content due to receipt of an interrupt content by the system. In addition, the hardware processor executes the content redirection software code to, during playout of the interrupt content by the system, save the playout status of the primary content at the pause. The hardware processor further executes the content redirection software code to detect completion of interrupt content playout by the system, and enable a return to the primary content after the pause.

Abstract: A process generates a certificate of authenticity for a virtual item. Further, the process sends, with the processor, the certificate of authenticity to a decentralized network of computing devices such that two or more of the computing devices store the certificate of authenticity. The two or more of the computing devices receive, from a user device that provides a virtual reality experience in which a virtual item is purchased, a request for authentication of the certificate of authenticity. In addition, the two or more computing devices authenticate the certificate of authenticity based on one or more consistency criteria for the certificate of authenticity being met by the two or more computing devices.

Abstract: In one implementation, an enhanced vision system includes a portable user device, a base station including a hardware processor and a memory storing a virtual effects rendering software code, and a display device communicatively coupled to the base station. The hardware processor executes the virtual effects rendering software code to detect the presence of the portable user device in a real-world environment, obtain a mapping of the real-world environment, and identify one or more virtual effect(s) for display in the real-world environment. The hardware processor further executes the virtual effects rendering software code to detect actuation of the portable user device, and to control the display device to display the virtual effect(s) in the real-world environment based on the mapping, and the position and orientation of the portable user device during the detected actuation.

Abstract: One embodiment of the present invention sets forth a technique for generating a content page having a plurality of layers. The technique includes detecting a first application event associated with a first layer included in a plurality of layers of a content page and accessing, via a template file, at least one parameter of the first layer that corresponds to the first application event. The technique further includes modifying at least one aspect of the first layer based on the first application event and the at least one parameter to generate a first modified layer, and outputting the first modified layer for display.

Abstract: An image processing system includes a computing platform having processing hardware, a display, and a system memory storing a software code. The processing hardware is configured to execute the software code to receive a three-dimensional (3D) digital model, surround the 3D digital model with multiple virtual cameras oriented toward the 3D digital model, and generate, using the virtual cameras, a multiple renders of the 3D digital model. The processing hardware is further configured to execute the software code to generate a UV texture coordinate space for a surface projection of the 3D digital model, and to transfer, using the multiple renders, lighting color values for each of multiple surface portions of the 3D digital model to the UV texture coordinate space.

Abstract: The exemplary embodiments relate to converting Standard Dynamic Range (SDR) content to High Dynamic Range (HDR) content using a machine learning system. In some embodiments, the neural network is trained to convert an input SDR image into an HDR image using the encoded representation of a training SDR image and a training HDR image. In other embodiments, the neural network is trained to convert an input SDR image into an HDR image using a predefined set of color grading actions and the training images.

Abstract: A system includes a hardware processor and a memory storing a software code including a predictive model. The hardware processor executes the software code to receive an input including an image having a pixel anomaly, and image data identifying the location of the pixel anomaly in the image. The software code uses the predictive model to extract a global feature map of a global image region of the image, the pixel anomaly being located within the global image region; to extract a local feature map of a local image region of the image, the pixel anomaly being located within the local image region and the local image region being smaller than the global image region; and to predict, based on the global feature map and the local feature map, a distraction level of the pixel anomaly within the image.

Abstract: A new controller for use in robots with kinematic loops as well as in most other types of robots (such as those with fully actuated kinematic trees). The controller includes an inverse kinematics (IK) module that implements a versatile IK formulation for retargeting of motions, including expressive motions, onto mechanical systems (i.e., robots with loops and/or without loops). Further, the controller is configured to support the precise control of the position and orientation of end effectors and the center of mass (CoM) (such as of walking robots). The formulation of the algorithms carried out by the IK module safeguards against a disassembly when IK targets are moved outside the workspace of the robot. A regularizer is included in the controller that smoothly circumvents kinematic singularities where velocities go to infinity.

Abstract: Systems and methods are presented for detecting physical contacts effectuated by actions performed by an entity participating in an event. An action, performed by the entity, is detected based on a sequence of pose data associated with the entity's performance in the event. A contact with another entity in the event is detected based on data associated with the detected action. The action and the contact detections are employed by neural-network based detectors.

Abstract: A computer-implemented method of changing a face within an output image or video frame includes: receiving an input image that includes a face presenting a facial expression in a pose; separately encoding different portions of the image by, for each separately encoded portion, generating a latent space point of the portion, thereby generating a plurality of multi-dimensional vectors where each multi-dimensional vector is an encoded representation of a different portion of the input image; concatenating the plurality of multi-dimensional vectors into a combined latent space vector; and decoding the combined latent space vector to generate the output image in accordance with a desired facial identity but with the facial expression and pose of the face in the input image

Abstract: A computer-implemented method of changing a face within an output image or video frame that includes: receiving an input image that includes a face presenting a facial expression in a pose; processing the image with a neural network encoder to generate a latent space point that is an encoded representation of the image; decoding the latent space point to generate an initial output image in accordance with a desired facial identity but with the facial expression and pose of the face in the input image; identifying a feature of the facial expression in the initial output image to edit; applying an adjustment vector to a latent space point corresponding to the initial output image to generate an adjusted latent space point; and decoding the adjusted latent space point to generate an adjusted output image in accordance with the desired facial identity but with the facial expression and pose of the face in the input image altered in accordance with the adjustment vector

Abstract: Certain aspects of the present disclosure provide techniques for automated updates to code deployment pipelines. This includes identifying a proposed change to a plurality of source code repositories based on parsing a change template. It further includes determining one or more changes to one or more files in each respective source code repository, of the plurality of source code repositories, based on the proposed change. It further includes changing the one or more files in each respective source code repository, based on the determined one or more changes, and building a project in each respective source code repository using the changed one or more files.

Abstract: In some implementations, a controller may cause a robotic arm connector, of the robotic arm, to be connected to a first compartment connector of a passenger compartment of an amusement ride. The controller may cause a second compartment connector, of the passenger compartment, to be disconnected from a first structure connector of a first support structure. The controller may transport the passenger compartment from the first support structure to a second support structure after causing the second compartment connector to be disconnected from the first structure connector.

Abstract: A system includes a machine learning (ML) model-based video downsampler configured to receive an input video sequence having a first display resolution, and to map the input video sequence to a lower resolution video sequence having a second display resolution lower than the first display resolution. The system also includes a neural network-based (NN-based) proxy video codec configured to transform the lower resolution video sequence into a decoded proxy bitstream. In addition, the system includes an upsampler configured to produce an output video sequence using the decoded proxy bitstream.

Abstract: This disclosure presents systems and methods to facilitate interaction by one or more participants with content presented across multiple distinct physical locations. A current distinct physical location of a participant may be determined. In response to determining the current distinct physical location in which the participant is located, operation of one or more content devices physically present in the current distinct physical location may be effectuated.

Abstract: Embodiments provide for a system, comprising a plurality of encoders configured to generate a plurality of variant streams, and a cross-variant Instantaneous Decoder Refresh (IDR) identifier configured to inspect the plurality of variant streams, identify IDR frames in each of the plurality of variant streams, determine which IDR frames correspond to cross-variant boundaries, and demarcate the IDR frames corresponding to cross-variant boundaries.

Abstract: There is provided a wireless portable device for providing location-based data to a user in a defined geographical area including a plurality of points of interest, the wireless portable device comprising a wireless transmitter, a wireless receiver, and a display. The wireless transmitter can transmit location information to a wireless server over a wireless network. The wireless receiver can receive location-based data relating to a point of interest from the wireless server periodically and automatically, based on the location of the wireless portable device. By optimizing map routes and schedules using the location-based data and user preferences including wish lists, the wireless portable device can provide helpful recommendations via the display, enabling the user to plan an efficient schedule of activities in the defined geographical area optimized by walking distance, queue wait times, booking and arriving at reserved events, and/or by other user preferences.

Abstract: A system includes a computing platform including processing hardware and a memory storing software code, a trained machine learning (ML) model, and a content thumbnail generator. The processing hardware executes the software code to receive interaction data describing interactions by a user with content thumbnails, identify, using the interaction data, an affinity by the user for at least one content thumbnail feature, and determine, using the interaction data, a predetermined business rule, or both, content for promotion to the user. The software code further provides a prediction, using the trained ML model and based on the affinity by the user, of the desirability of each of multiple candidate thumbnails for the content to the user, generates, using the content thumbnail generator and based on the prediction, a thumbnail having features of one or more of the candidate thumbnails, and displays the thumbnail to promote the content to the user.

Abstract: A system includes a hardware processor that executes a software code to receive an authorization request on behalf of a user for a stacked resource including resources offered separately by multiple resource providers, determine resource provider computers associated with the stacked resource, and send a look-up request including an electronic identity of the user to those computers, where the electronic identity is used as a look-up key for determining user attribute(s) of the user. The software code further receives the user attribute(s) from the resource provider computers, generates an accumulated access profile of the user based on the user attribute(s), applies the profile to a rules engine to determine a stacked access result, and routes the authorization request and the stacked access result to one of the resource provider computers, where that computer completes an authorization process for access to the stacked resource based on the stacked access result.

Abstract: A method and device generates a fantasy sports recommendation. The method includes receiving a plurality of ranking values associated with a sport player, each of the ranking values being generated from a respective source. The method includes assigning a weight value to each of the ranking values, the weight value being associated with the respective source. The method includes generating a recommendation value for the sport player as a function of the ranking values and the corresponding weight values. The method includes receiving a selection value for the sport player. The method includes determining a further weight value for each of the sources as a function of the selection value, the recommendation value, and the weight value for the corresponding source.