An image processing system includes a computing platform having processing hardware, a display, and a system memory storing a software code. The processing hardware executes the software code to receive a digital object, surround the digital object with virtual cameras oriented toward the digital object, render, using each one of the virtual cameras, a depth map identifying a distance of that one of the virtual cameras from the digital object, and generate, using the depth map, a volumetric perspective of the digital object from a perspective of that one of the virtual cameras, resulting in multiple volumetric perspectives of the digital object. The processing hardware further executes the software code to merge the multiple volumetric perspectives of the digital object to form a volumetric representation of the digital object, and to convert the volumetric representation of the digital object to a renderable form.

An image processing system includes a computing platform having processing hardware, a display, and a system memory storing a software code. The processing hardware executes the software code to receive a digital object, surround the digital object with virtual cameras oriented toward the digital object, render, using each one of the virtual cameras, a depth map identifying a distance of that one of the virtual cameras from the digital object, and generate, using the depth map, a volumetric perspective of the digital object from a perspective of that one of the virtual cameras, resulting in multiple volumetric perspectives of the digital object. The processing hardware further executes the software code to merge the multiple volumetric perspectives of the digital object to form a volumetric representation of the digital object, and to convert the volumetric representation of the digital object to a renderable form.

Systems, methods, tangible non-transitory computer-readable media, and devices for autonomous vehicle operation are provided. For example, a computing system can receive object data that includes portions of sensor data. The computing system can determine, in a first stage of a multiple stage classification using hardware components, one or more first stage characteristics of the portions of sensor data based on a first machine-learned model. In a second stage of the multiple stage classification, the computing system can determine second stage characteristics of the portions of sensor data based on a second machine-learned model. The computing system can generate an object output based on the first stage characteristics and the second stage characteristics. The object output can include indications associated with detection of objects in the portions of sensor data.

Systems, methods, tangible non-transitory computer-readable media, and devices for autonomous vehicle operation are provided. For example, a computing system can receive object data that includes portions of sensor data. The computing system can determine, in a first stage of a multiple stage classification using hardware components, one or more first stage characteristics of the portions of sensor data based on a first machine-learned model. In a second stage of the multiple stage classification, the computing system can determine second stage characteristics of the portions of sensor data based on a second machine-learned model. The computing system can generate an object output based on the first stage characteristics and the second stage characteristics. The object output can include indications associated with detection of objects in the portions of sensor data.

A computer-implemented method for use in determining a radiation dose distribution in a medical volume, comprises: receiving a volumetric dataset representing the medical volume; performing a selection process of a rendering process for generating a visualization of the volumetric dataset to select at least one sample point in the volumetric dataset on which to perform a radiation determination process; and performing, for the at least one sample point in the volumetric dataset, the radiation dose determination process to determine a radiation dose at the at least one sample point. The method may also include visualizing the volumetric dataset and/or the radiation dose distribution.

A computer-implemented method for use in determining a radiation dose distribution in a medical volume, comprises: receiving a volumetric dataset representing the medical volume; performing a selection process of a rendering process for generating a visualization of the volumetric dataset to select at least one sample point in the volumetric dataset on which to perform a radiation determination process; and performing, for the at least one sample point in the volumetric dataset, the radiation dose determination process to determine a radiation dose at the at least one sample point. The method may also include visualizing the volumetric dataset and/or the radiation dose distribution.

Embodiments of the present disclosure relate to a three-dimensional reconstruction method and apparatus for a material pile, an electronic device, and a computer-readable medium. The method may include: acquiring, in response to an instruction for controlling an excavator body of an excavator to rotate to transport materials being detected, a sequence of depth images of an excavated material pile collected by a binocular camera provided on a side of the excavator; and performing three-dimensional reconstruction based on the sequence of depth images of the material pile, to generate a three-dimensional model of the material pile.

Embodiments of the present disclosure relate to a three-dimensional reconstruction method and apparatus for a material pile, an electronic device, and a computer-readable medium. The method may include: acquiring, in response to an instruction for controlling an excavator body of an excavator to rotate to transport materials being detected, a sequence of depth images of an excavated material pile collected by a binocular camera provided on a side of the excavator; and performing three-dimensional reconstruction based on the sequence of depth images of the material pile, to generate a three-dimensional model of the material pile.

Ray tracing systems have computation units (“RACs”) adapted to perform ray tracing operations (e.g. intersection testing). There are multiple RACs. A centralized packet unit controls the allocation and testing of rays by the RACs. This allows RACs to be implemented without Content Addressable Memories (CAMs) which are expensive to implement, but the functionality of CAMs can still be achieved by implemented them in the centralized controller.

Ray tracing systems have computation units (“RACs”) adapted to perform ray tracing operations (e.g. intersection testing). There are multiple RACs. A centralized packet unit controls the allocation and testing of rays by the RACs. This allows RACs to be implemented without Content Addressable Memories (CAMs) which are expensive to implement, but the functionality of CAMs can still be achieved by implemented them in the centralized controller.