Abstract: Systems and methods for tone mapping of high dynamic range (HDR) images for high-quality deep learning based processing are disclosed. In one embodiment, a graphics processor includes a media pipeline to generate media requests for processing images and an execution unit to receive media requests from the media pipeline. The execution unit is configured to compute an auto-exposure scale for an image to effectively tone map the image, to scale the image with the computed auto-exposure scale, and to apply a tone mapping operator including a log function to the image and scaling the log function to generate a tone mapped image.

Abstract: Systems and methods for tone mapping of high dynamic range (HDR) images for high-quality deep learning based processing are disclosed. In one embodiment, a graphics processor includes a media pipeline to generate media requests for processing images and an execution unit to receive media requests from the media pipeline. The execution unit is configured to compute an auto-exposure scale for an image to effectively tone map the image, to scale the image with the computed auto-exposure scale, and to apply a tone mapping operator including a log function to the image and scaling the log function to generate a tone mapped image.

Abstract: Apparatus and method for double-precision traversal and intersection.

Abstract: The present disclosure provides an apparatus and method of guided neural network model for image processing. An apparatus may comprise a guidance map generator, a synthesis network and an accelerator. The guidance map generator may receive a first image as a content image and a second image as a style image, and generate a first plurality of guidance maps and a second plurality of guidance maps, respectively from the first image and the second image. The synthesis network may synthesize the first plurality of guidance maps and the second plurality of guidance maps to determine guidance information. The accelerator may generate an output image by applying the style of the second image to the first image based on the guidance information.

Abstract: Apparatus and method for non-local means filtering using a media processing block of a graphics processor. For example, one embodiment of a processor comprises: ray tracing circuitry to execute a first set of one or more commands to traverse rays through a bounding volume hierarchy (BVH) to identify BVH nodes and/or primitives intersected by the ray; shader execution circuitry to execute one or more shaders responsive to a second set of one or more commands to render a sequence of image frames based on the BVH nodes and/or primitives intersected by the ray; and a media processor comprising motion estimation circuitry to execute a third set of one or more commands to perform non-local means filtering to remove noise from the sequence of image frames based on a mean pixel value collected across the sequence of image frames.

Abstract: The present disclosure provides an apparatus and method of guided neural network model for image processing. An apparatus may comprise a guidance map generator, a synthesis network and an accelerator. The guidance map generator may receive a first image as a content image and a second image as a style image, and generate a first plurality of guidance maps and a second plurality of guidance maps, respectively from the first image and the second image. The synthesis network may synthesize the first plurality of guidance maps and the second plurality of guidance maps to determine guidance information. The accelerator may generate an output image by applying the style of the second image to the first image based on the guidance information.

Abstract: Systems and methods for tone mapping of high dynamic range (HDR) images for high-quality deep learning based processing are disclosed. In one embodiment, a graphics processor includes a media pipeline to generate media requests for processing images and an execution unit to receive media requests from the media pipeline. The execution unit is configured to compute an auto-exposure scale for an image to effectively tone map the image, to scale the image with the computed auto-exposure scale, and to apply a tone mapping operator including a log function to the image and scaling the log function to generate a tone mapped image.

Abstract: Systems and methods for tone mapping of high dynamic range (HDR) images for high-quality deep learning based processing are disclosed. In one embodiment, a graphics processor includes a media pipeline to generate media requests for processing images and an execution unit to receive media requests from the media pipeline. The execution unit is configured to compute an auto-exposure scale for an image to effectively tone map the image, to scale the image with the computed auto-exposure scale, and to apply a tone mapping operator including a log function to the image and scaling the log function to generate a tone mapped image.

Abstract: Systems and methods for tone mapping of high dynamic range (HDR) images for high-quality deep learning based processing are disclosed. In one embodiment, a graphics processor includes a media pipeline to generate media requests for processing images and an execution unit to receive media requests from the media pipeline. The execution unit is configured to compute an auto-exposure scale for an image to effectively tone map the image, to scale the image with the computed auto-exposure scale, and to apply a tone mapping operator including a log function to the image and scaling the log function to generate a tone mapped image.

Abstract: Apparatus and method for non-local means filtering using a media processing block of a graphics processor. For example, one embodiment of a processor comprises: ray tracing circuitry to execute a first set of one or more commands to traverse rays through a bounding volume hierarchy (BVH) to identify BVH nodes and/or primitives intersected by the ray; shader execution circuitry to execute one or more shaders responsive to a second set of one or more commands to render a sequence of image frames based on the BVH nodes and/or primitives intersected by the ray; and a media processor comprising motion estimation circuitry to execute a third set of one or more commands to perform non-local means filtering to remove noise from the sequence of image frames based on a mean pixel value collected across the sequence of image frames.

Abstract: Systems and methods for tone mapping of high dynamic range (HDR) images for high-quality deep learning based processing are disclosed. In one embodiment, a graphics processor includes a media pipeline to generate media requests for processing images and an execution unit to receive media requests from the media pipeline. The execution unit is configured to compute an auto-exposure scale for an image to effectively tone map the image, to scale the image with the computed auto-exposure scale, and to apply a tone mapping operator including a log function to the image and scaling the log function to generate a tone mapped image.

Abstract: The present disclosure provides an apparatus and method of guided neural network model for image processing. An apparatus may comprise a guidance map generator, a synthesis network and an accelerator. The guidance map generator may receive a first image as a content image and a second image as a style image, and generate a first plurality of guidance maps and a second plurality of guidance maps, respectively from the first image and the second image. The synthesis network may synthesize the first plurality of guidance maps and the second plurality of guidance maps to determine guidance information. The accelerator may generate an output image by applying the style of the second image to the first image based on the guidance information.

Abstract: Embodiments are generally directed to a Conditional Kernel Prediction Network (CKPN) for image and video de-noising and other related image and video processing applications. Disclosed is an embodiment of a method for de-noising an image or video frame by a convolutional neural network implemented on a compute engine, the image including a plurality of pixels, the method comprising: for each of the plurality of pixels of the image, generating a convolutional kernel having a plurality of kernel weights for the pixel, the plurality of kernel weights respectively corresponding to pixels within a region surrounding the pixel; adjusting the plurality of kernel weights of the convolutional kernel for the pixel based on convolutional kernels generated respectively for the corresponding pixels within the region surrounding the pixel; and filtering the pixel with the adjusted plurality of kernel weights and pixel values of the corresponding pixels within the region surrounding the pixel to obtain a de-noised pixel.

Abstract: Apparatus and method for double-precision traversal and intersection.

Abstract: Apparatus and method for non-local means filtering using a media processing block of a graphics processor. For example, one embodiment of a processor comprises: ray tracing circuitry to execute a first set of one or more commands to traverse rays through a bounding volume hierarchy (BVH) to identify BVH nodes and/or primitives intersected by the ray; shader execution circuitry to execute one or more shaders responsive to a second set of one or more commands to render a sequence of image frames based on the BVH nodes and/or primitives intersected by the ray; and a media processor comprising motion estimation circuitry to execute a third set of one or more commands to perform non-local means filtering to remove noise from the sequence of image frames based on a mean pixel value collected across the sequence of image frames.

Abstract: Systems and methods for tone mapping of high dynamic range (HDR) images for high-quality deep learning based processing are disclosed. In one embodiment, a graphics processor includes a media pipeline to generate media requests for processing images and an execution unit to receive media requests from the media pipeline. The execution unit is configured to compute an auto-exposure scale for an image to effectively tone map the image, to scale the image with the computed auto-exposure scale, and to apply a tone mapping operator including a log function to the image and scaling the log function to generate a tone mapped image.

Abstract: Apparatus and method for improving denoising of images generated by a rendering engine such as a ray tracing engine. For example, one embodiment renders a first plurality of images during runtime using a first sample count. Denoising is performed on the first plurality of images during runtime by a machine-learning engine. In addition, a reference region is generated from one or more of the first plurality of images at a second sample count which is greater than the first sample count. The reference region is then used to perform additional runtime training of the machine-learning engine.

Abstract: Apparatus and method for improving denoising of images generated by a rendering engine such as a ray tracing engine. For example, one embodiment renders a first plurality of images during runtime using a first sample count. Denoising is performed on the first plurality of images during runtime by a machine-learning engine. In addition, a reference region is generated from one or more of the first plurality of images at a second sample count which is greater than the first sample count. The reference region is then used to perform additional runtime training of the machine-learning engine.

Abstract: A graphics processing apparatus comprising bounding volume hierarchy (BVH) construction circuitry to perform a spatial analysis and temporal analysis related to a plurality of input primitives and responsively generate a BVH comprising spatial, temporal, and spatial-temporal components that are hierarchically arranged, wherein the spatial components include a plurality of spatial nodes with children, the spatial nodes bounding the children using spatial bounds, and the temporal components comprise temporal nodes with children, the temporal nodes bounding their children using temporal bounds and the spatial-temporal components comprise spatial-temporal nodes with children, the spatial-temporal nodes bounding their children using spatial and temporal bounds; and ray traversal/intersection circuitry to traverse a ray or a set of rays through the BVH in accordance with the spatial and temporal components.