Abstract: A safety system for a vehicle may include one or more processors configured to determine uncertainty data indicating uncertainty in one or more predictions from a driving model during operation of a vehicle; change or update one or more of the driving model parameters to one or more changed or updated driving model parameters based on the determined uncertainty data; and provide the one or more changed or updated driving model parameters to a control system of the vehicle for controlling the vehicle to operate in accordance with the driving model including the one or more changed or updated driving model parameters.

Abstract: Embodiments are directed to artificial intelligence (AI) analysis and explanation utilizing hardware measures of attention. An embodiment of a non-transitory computer-readable storage medium has stored thereon executable computer program instructions for: monitoring one or more factors of an AI network during operation of the network, the network to receive input data and output a decision based at least in part on the input data; determining attention received by the one or more factors of the network during the operation of the network; determining one or more relationships between the attention received by the one or more factors and a decision of the network based at least in part on the monitored information; and generating an analysis of the operation of the network based at least in part on the one or more relationships between attention received by the one or more factors and the decision of the network.

Abstract: According to various embodiments, devices, methods, and computer-readable media for reconstructing a 3D scene are described. A server device, sensor devices, and client devices may interoperate to reconstruct a 3D scene sensed by the sensor devices. The server device may generate one or more models for objects in the scene, including the identification of dynamic and/or static objects. The sensor devices may, provide model data updates based on these generated models, such that only delta changes in the scene may be provided, in addition to raw sensor data. Models may utilize semantic knowledge, such as knowledge of the venue or identity of one or more persons in the scene, to further facilitate model generation and updating. Other embodiments may be described and/or claimed.

Abstract: According to various embodiments, devices, methods, and computer-readable media for reconstructing a 3D scene are described. A server device, sensor devices, and client devices may interoperate to reconstruct a 3D scene sensed by the sensor devices. The server device may generate one or more models for objects in the scene, including the identification of dynamic and/or static objects. The sensor devices may, provide model data updates based on these generated models, such that only delta changes in the scene may be provided, in addition to raw sensor data. Models may utilize semantic knowledge, such as knowledge of the venue or identity of one or more persons in the scene, to further facilitate model generation and updating. Other embodiments may be described and/or claimed.

Abstract: Techniques are provided for 3D model reconstruction of dynamic scenes using hybrid foreground-background processing. A methodology implementing the techniques according to an embodiment includes receiving multiple static images of a scene. Each static image is generated by a static camera, positioned at a fixed location and oriented at a fixed viewing angle. The method also includes receiving multiple dynamic images of the scene, each dynamic image generated by a movable camera. The method further includes performing 3D reconstruction of the scene foreground, based on the static images, and performing 3D reconstruction of the scene background, based on the static images and the dynamic images. The method further includes superimposing the reconstructed 3D foreground and 3D background, with alignment based on calibration parameters (e.g., focal length, principal point, rotation, or translation) of the static and movable cameras, to provide a hybrid 3D reconstruction of the scene for 3D rendering.

Abstract: According to various embodiments, devices, methods, and computer-readable media for reconstructing a 3D scene are described. A server device, sensor devices, and client devices may interoperate to reconstruct a 3D scene sensed by the sensor devices. The server device may generate one or more models for objects in the scene, including the identification of dynamic and/or static objects. The sensor devices may, provide model data updates based on these generated models, such that only delta changes in the scene may be provided, in addition to raw sensor data. Models may utilize semantic knowledge, such as knowledge of the venue or identity of one or more persons in the scene, to further facilitate model generation and updating. Other embodiments may be described and/or claimed.