Abstract: The systems herein include a support structure and multiple light sources mounted to the support structure. The light sources are configured to project light onto a recording stage to light a specified video scene that is to be recorded on the recording stage. These systems also include a perforated layer that includes an arrangement of apertures. The perforated layer has an inward face directed toward the lighting sources and an outward face directed toward the recording stage. The inward face of the perforated layer includes a surface layer that is more reflective than the surface layer of the outward face of the perforated layer. These systems also include a controller that modifies the light emission profile of the light sources, including changing color balance, brightness, time dependence, and/or spatial variation over the light emissive surface of the light sources. Various other apparatuses and recording stage devices are also disclosed.

Abstract: In various embodiments, a content platform receives, from a user device, a request for a web page. In response to receiving the request for the web page, the content platform retrieves one or more page construction items associated with the web page and one or more page content items associated with the web page, wherein each page construction item included in the one or more page construction items indicates a structure of a different element included in the web page and each page content item included in the one or more page content items indicates a content of a different element included in the web page. The content platform generates a content interface associated with the web page based on the one or more page construction items, the one or more page content items, and user data associated with a user of the user device.

Abstract: The disclosed computer-implemented method may include receiving, from a client device, a request for multimedia content, where the request includes both a manifest request that includes client identification data and a license request that includes a license challenge. The method may further include validating the received request for multimedia content using the client identification data in the manifest request and generating a manifest response that includes an identification of a specified multimedia content stream that is to be provided to the client device. The method may also include acquiring at least one license in response to the license request, where the license includes a response to the license challenge having various content keys, and then providing the specified multimedia content stream, including the generated manifest response and the acquired license, to the client device. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: In various embodiments, a serverless function agent determines that a client stub function has been invoked with a first set of arguments in a first execution environment. The serverless function agent then performs one or more operations on a media item that is associated with a first argument included in the first set of arguments to generate a second argument included in a second set of arguments. Notably, the first argument has a first data type and the second argument has a second data type. Subsequently, the serverless function agent invokes a function with the second set of arguments in a second execution environment. Advantageously, because the serverless function agent automatically performs operations on the media item, the overall amount of technical know-how and manual effort required to enable the function to successfully execute on a wide range of media items can be reduced.

Abstract: The disclosed computer-implemented method may include systems and methods for automatically generating sound event subtitles for digital videos. For example, the systems and methods described herein can automatically generate subtitles for sound events within a digital video soundtrack that includes sounds other than speech. Additionally, the systems and methods described herein can automatically generate sound event subtitles as part of an automatic and comprehensive approach that generates subtitles for all sounds within a soundtrack of a digital video—thereby avoiding the need for any manual inputs as part of the subtitling process.

Abstract: In various embodiments, a bootstrapping training subsystem performs sampling operation(s) on a training database that includes subjective scores to generate resampled dataset. For each resampled dataset, the bootstrapping training subsystem performs machine learning operation(s) to generate a different bootstrap perceptual quality model. The bootstrapping training subsystem then uses the bootstrap perceptual quality models to quantify the accuracy of a perceptual quality score generated by a baseline perceptual quality model for a portion of encoded video content. Advantageously, relative to prior art solutions in which the accuracy of a perceptual quality score is unknown, the bootstrap perceptual quality models enable developers and software applications to draw more valid conclusions and/or more reliably optimize encoding operations based on the perceptual quality score.

Abstract: Various embodiments set forth systems and techniques for securing media content capture capabilities on a device. The techniques include receiving a frame of a media content item; determining whether the frame of the media content item is signed based on an analysis of one or more pixels of the frame; and when the media content is signed, removing one or more restrictions on one or more functions on the device based on whether the one or more pixels on the frame meet one or more conditions, wherein the one or more functions enable the device to perform one or more operations on the frame of the media content item.

Abstract: Techniques are disclosed for improving user experience of multimedia streaming over computer networks. More specifically, techniques presented herein reduce (or eliminate) latency in playback start time for streaming digital media content resulting from digital rights management (DRM) authorizations. A streaming media client (e.g., a browser, set-top box, mobile telephone or tablet “app”) may request a “fast-expiring” license for titles the streaming media client predicts a user is likely to begin streaming. A fast-expiring license is a DRM license (and associated decryption key) which is valid for only a very limited time after being used for playback. During the validity period of such a license, the client device requests a “normal” or “regular” license to continue accessing the title after the fast-expiring license expires.

Abstract: In various embodiments, a manifest customization application generates presentations of media titles for playback. The manifest customization application selects a first set of video streams from multiple sets of video steams that are associated with a media title and included in a media package video streams based on a first preference associated with a user. The manifest customization application selects a first set audio streams from multiple sets of audio streams included in the media package based on a second preference associated with the user. The manifest customization application generates a recommended presentation based on the first set of video streams and the first set of audio streams. The manifest customization application generates a manifest file that allows the media title to be played back in accordance with at least the recommended presentation.

Abstract: The disclosed computer-implemented methods and systems include pausing a digital content stream being provided to a display device in response to determining that the display device is powered off. For example, rather than utilizing signals related to the power status of the display device, the disclosed methods and systems utilize signals related to display protocols and interfaces utilized by the display device to determine its power status. In response to determining that a display device is powered off, the disclosed methods and systems can pause the digital content stream being provided to the display device. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: The disclosed computer-implemented method may include predicting, by a machine learning model, a user action and a timing of the user action for an application on a computing device. The method may also include determining that an expected lag in executing the user action is greater than a predetermined threshold based on one or more resource constraints of the computing device and initializing a setup of the application to reduce the expected lag in executing the user action based on the predicted timing. Furthermore, the method may include prefetching one or more application components in response to initializing the setup of the application and preprocessing at least a portion of a function of the application used to execute the user action. Finally, the method may include executing the user action for the application in response to a user request. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: In various embodiments, servers in a server pool share a centrally-generated encryption key that is used to encrypt session keys in tickets that can be used by client applications to share secure communication sessions across different servers belonging to the same server pools. When the client application first establishes a secure communication session with a server in a server pool, the server returns a ticket that includes an encrypted version of a session key generated using an encryption key shared by servers in the server pool. Thereafter, the client application can present the ticket to other servers in the server pool to restore the secure communication session with the other servers. Associations between servers and server pools can be communicated to the client application in any technically feasible manner, such as part of information indicating servers from which content can be accessed or via the Domain Name System (DNS).

Abstract: In various embodiments, a caching application streams segments of a downloadable to a client device. At a first point-in-time, the caching application receives a first request for a first segment of the downloadable from the client device. The caching application computes a cache key based on a request Uniform Resource Locator included in the first request and a version identifier associated with the downloadable. The caching application determines that no segment corresponding to the cache key is stored in a cache. The caching application transmits a second request for the first segment to a different server. Upon receiving a first version of the first segment from the different server, the caching server transmits a response that includes the first version of the first segment to the client device.

Abstract: The disclosed computer-implemented method may include receiving, as input, an audio/video data object; isolating a video stream of a visible potential speaker over a plurality of frames of the audio/video data object; isolating an audio stream over the plurality of frames; providing the isolated video stream and the isolated audio stream to a machine learning model trained with contrastive learning, the contrastive learning using (i) a corpus of video segments of visible speakers with corresponding original audio for positive samples; and (ii) a corpus of video segments of visible speakers with corresponding dubbed audio for negative samples; and evaluating a match between the isolated audio stream and the isolated video stream based at least in part on an output of the machine learning model. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: The disclosed computer-implemented method includes applying transport protocol heuristics to selective acknowledgement (SACK) messages received at a network adapter from a network node. The transport protocol heuristics identify threshold values for operational functions that are performed when processing the SACK messages. The method further includes determining, by applying the transport protocol heuristics to the SACK messages received from the network node, that the threshold values for the transport protocol heuristics have been reached. In response to determining that the threshold values have been reached, the method includes identifying the network node as a security threat and taking remedial actions to mitigate the security threat. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: The disclosed computer-implemented method includes systems for optimizing color rendition in an LED volume virtual production stage. For example, the described systems optimize or correct color rendition by applying a series of color correction matrices to color pixel values within the virtual production stage and to final captured imagery filmed within the virtual production stage. The described systems generate the color correction matrices from four calibration images taken within the virtual production stage. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: One embodiment of the invention sets forth a mechanism for encoding video streams associated with the same digital content such that switch points staggered across two video streams occur at every offset temporal distance. The offset temporal distance is less than the distance between two consecutive key frames in a given video stream. This enables a content player to switch to a video stream having a playback quality up or down one level from a current video stream at the offset temporal distance from the most recently played key frame. In effect, the content player does not wait the entire key frame temporal distance before switching.

Abstract: The disclosed computer-implemented method may include accessing a media item that includes multiple media item segments that are to be played back in a specific manner. The method may also include generating playgraphs for the media item, where the playgraphs define different playback paths between media item segments. The method may next include selecting a specific playgraph from the generated playgraphs, and then providing the selected playgraph to a playback device. Playback of the media item according to the selected playgraph may thereby provide a customized presentation of the media item. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: One embodiment of the present invention sets forth a technique for selecting a frame of video content that is representative of a media title. The technique includes applying an embedding model to a plurality of faces included in a set of frames of the video content to generate a plurality of face embeddings. The technique also includes aggregating the plurality of face embeddings into a plurality of clusters representing a plurality of characters included in the media title. The technique further includes computing a plurality of prominence scores for the plurality of characters based on one or more attributes of the plurality of clusters, and selecting, from the set of frames, a frame of video content as representative of the media title based on one or more prominence scores for one or more characters included in the frame.

Abstract: In various embodiments, a training application trains a convolutional neural network to downsample images in a video encoding pipeline. The convolution neural network includes at least two residual blocks and is associated with a downsampling factor. The training application executes the convolutional neural network on a source image to generate a downsampled image. The training application then executes an upsampling algorithm on the downsampled image to generate a reconstructed image having the same resolution as the source image. The training application computes a reconstruction error based on the reconstructed image and the source image. The training application updates at least one parameter of the convolutional neural network based on the reconstruction error to generate a trained convolutional neural network.