Abstract: One or more embodiments of the present disclosure relate to generation of map data. In these or other embodiments, the generation of the map data may include determining whether objects indicated by the sensor data are static objects or dynamic objects. Additionally or alternatively, sensor data may be removed or included in the map data based on determinations as to whether it corresponds to static objects or dynamic objects.

Abstract: Systems and methods are disclosed that relate to testing processing elements of an integrated processing system. A first system test may be performed on a first processing element of an integrated processing system. The first system test may be based at least on accessing a test node associated with the first processing element. The first system test may be accessed using a first local test controller. A second system test may be performed on a second processing element of the integrated processing system. The second system test may be based at least on accessing a second test node associated with the second processing element. The second system test may be accessed using a second local test controller.

Abstract: In various examples, systems and methods are disclosed relating to aligning images into frames of a first video using at least one first temporal attention layer of a neural network model. The first video has a first spatial resolution. A second video having a second spatial resolution is generated by up-sampling the first video using at least one second temporal attention layer of an up-sampler neural network model, wherein the second spatial resolution is higher than the first spatial resolution.

Abstract: Systems, computer program products, and methods are described herein for automated data retrieval from an integrated circuit (IC). An example system extracts, using a scan island (e.g., a partition of the IC that is isolated for data retrieval), data from a plurality of scan chains and a plurality of random-access memories (RAMs) associated with the IC in response to a trigger event associated with the IC; determines, using a data security module associated with the scan island, whether the one or more users are authorized to access the respective portions of the data; and transmits the one or more portions of the data to the one or more users upon verification of their authorization.

Abstract: Approaches presented herein provide for the optimization of tasks performed for an operation such as the rendering of an image. A Frame Interceptor (FI) can generate a resource dependency graph (RDG) by intercepting API calls during the rendering process and determining dependencies. FI can analyze the RDG to identify potential optimizations, such as may correspond to reordering or parallel execution of certain tasks. FI can automatically test optimizations to determine whether sufficient improvement is obtained. This testing can be performed in real time by replacing the originally intercepted API calls with the newly ordered API calls generated by FI. FI can then issue a report that indicates information such as the changes made, the time taken to render the image, and potentially the fact that the images were determined to be identical.

Abstract: A game-agnostic event detector can be used to automatically identify game events. Game-specific configuration data can be used to specify types of pre-processing to be performed on media for a game session, as well as types of detectors to be used to detect events for the game. Event data for detected events can be written to an event log in a form that is both human- and process-readable. The event data can be used for various purposes, such as to generate highlight videos or provide player performance feedback. The event data may be determined based upon output from detectors such as optical character recognition (OCR) engines, and the regions may be upscaled and binarized before OCR processing.

Abstract: In various examples, estimated field of view or gaze information of a user may be projected external to a vehicle and compared to vehicle perception information corresponding to an environment outside of the vehicle. As a result, interior monitoring of a driver or occupant of the vehicle may be used to determine whether the driver or occupant has processed or seen certain object types, environmental conditions, or other information exterior to the vehicle. For a more holistic understanding of the state of the user, attentiveness and/or cognitive load of the user may be monitored to determine whether one or more actions should be taken. As a result, notifications, AEB system activations, and/or other actions may be determined based on a more complete state of the user as determined based on cognitive load, attentiveness, and/or a comparison between external perception of the vehicle and estimated perception of the user.

Abstract: Systems and methods of compressing video content as encoded data and selectively reconstructing portions of the content are disclosed. The proposed systems provide a computer-implemented process configured to classify a person's behavior(s) during a video and encode the behaviors as a representation of the video. When playback of the video is requested, a video navigation assistant will allow the end-user to select specific segments of the video based on topics discussed in the video and the codes that were generated to represent the video. The user is then able to move through segments of the video in a sequence that aligns with their viewing preferences.

Abstract: In various examples, sensor configuration for autonomous or semi-autonomous systems and applications is described. Systems and methods are disclosed that may use image feature correspondences between camera images along with an assumption that image features are locally planar to determine parameters for calibrating an image sensor with a LiDAR sensor and/or another image sensor. In some examples, an optimization problem is constructed that attempts to minimize a geometric loss function, where the geometric loss function encodes the notion that corresponding image features are views of a same point on a locally planar surface (e.g., a surfel or mesh) that is constructed from LiDAR data generated using a LiDAR sensor. In some examples, performing such processes to determine the calibration parameters may remove structure estimation from the optimization problem.

Abstract: In various examples, a three-dimensional (3D) intersection structure may be predicted using a deep neural network (DNN) based on processing two-dimensional (2D) input data. To train the DNN to accurately predict 3D intersection structures from 2D inputs, the DNN may be trained using a first loss function that compares 3D outputs of the DNN—after conversion to 2D space—to 2D ground truth data and a second loss function that analyzes the 3D predictions of the DNN in view of one or more geometric constraints—e.g., geometric knowledge of intersections may be used to penalize predictions of the DNN that do not align with known intersection and/or road structure geometries. As such, live perception of an autonomous or semi-autonomous vehicle may be used by the DNN to detect 3D locations of intersection structures from 2D inputs.

Abstract: In various examples, high-precision semantic image editing for machine learning systems and applications are described. For example, a generative adversarial network (GAN) may be used to jointly model images and their semantic segmentations based on a same underlying latent code. Image editing may be achieved by using segmentation mask modifications (e.g., provided by a user, or otherwise) to optimize the latent code to be consistent with the updated segmentation, thus effectively changing the original, e.g., RGB image. To improve efficiency of the system, and to not require optimizations for each edit on each image, editing vectors may be learned in latent space that realize the edits, and that can be directly applied on other images with or without additional optimizations. As a result, a GAN in combination with the optimization approaches described herein may simultaneously allow for high precision editing in real-time with straightforward compositionality of multiple edits.

Abstract: Disclosed are systems and methods relating to extracting 3D features, such as bounding boxes. The systems can apply, to one or more features of a source image that depicts a scene using a first set of camera parameters, based on a condition view image associated with the source image, an epipolar geometric warping to determine a second set of camera parameters. The systems can generate, using a neural network, a synthetic image representing the one or more features and corresponding to the second set of camera parameters.

Abstract: Apparatuses, systems, and techniques to determine a matrix multiplication algorithm for a matrix multiplication operation. In at least one embodiment, a matrix multiplication operation is analyzed to determine an appropriate matrix multiplication algorithm to perform the matrix multiplication algorithm.

Abstract: In various examples, audio alerts of emergency response vehicles may be detected and classified using audio captured by microphones of an autonomous or semi-autonomous machine in order to identify travel directions, locations, and/or types of emergency response vehicles in the environment. For example, a plurality of microphone arrays may be disposed on an autonomous or semi-autonomous machine and used to generate audio signals corresponding to sounds in the environment. These audio signals may be processed to determine a location and/or direction of travel of an emergency response vehicle (e.g., using triangulation). Additionally, to identify siren types—and thus emergency response vehicle types corresponding thereto—the audio signals may be used to generate representations of a frequency spectrum that may be processed using a deep neural network (DNN) that outputs probabilities of alert types being represented by the audio data.

Abstract: A cluster storage system takes snapshots that are consistent across all storage nodes. The storage system can nearly instantaneously promote a set of consistent snapshots to their respective base volumes to restore the base volumes to be the same as the snapshots. Given these two capabilities, users can restore the system to a recovery point of the user's choice, by turning off storage service I/O, promoting the snapshots constituting the recovery point, rebooting their servers, and resuming storage service I/O.

Abstract: Apparatuses, systems, and techniques to generate blue noise masks for real-time image rendering and enhancement. In at least one embodiment, a noise mask is generated and applied to one or more images to generate one or more enhanced images for image processing (e.g., real-time image rendering). In at least one embodiment, the noise mask is able to handle the temporal domain (e.g., add time to the spatial domain) to improve image quality when rendering images over multiple frames.

Abstract: In various examples, systems and methods are disclosed relating to bandwidth preservation through selective application of error mitigation techniques for video frame regions. A subset of network packets for a video stream are identified as corresponding to an encoded region of a video frame of the video stream. At least one error correction packet is transmitted for the subset that encodes the region of the video frame. The network packets and the at least one error correction packet can be transmitted to a receiver device.

Abstract: systems, computer program products, and methods are described for an endpoint device configured for secure data transmission within a network. An example endpoint device may include a network interface configured to receive a communication request from a peer endpoint device, and an access control unit configured to determine whether a peer endpoint device is IDE qualified based on the communication request. If the peer endpoint device is IDE qualified, the access control unit authorizes the communication request, allowing secure communication between the devices. If the peer endpoint device is not IDE qualified, the access control unit transmits the communication request to a root port for further authorization, verifying that only IDE-qualified devices are permitted to communicate directly.

Abstract: In various examples, systems and methods are disclosed relating to improving perceived video quality through temporal redistribution of network packet payloads that may carry error mitigation data. A subset of network packets for an encoded video stream is identified from a sequence of network packets as corresponding to a region of a video frame of the encoded video stream. A transmission order for the sequence of network packets is determined based at least on the subset of network packets and one or more error correction packets corresponding to the sequence of network packets. The sequence of network packets is transmitted to a receiver client device according to the transmission order.

Abstract: In various examples, systems and methods are disclosed relating to error concealment by replacing a lost video frame region with a chronological predecessor. Network packets including data corresponding to an encoded bitstream of a frame of a video stream can be received. In response to determining that at least one packet of the video stream has been lost, a region of the video frame corresponding to the lost network packet can be replaced with the same region of a previous frame of the video stream.