SAMPLE DISTRIBUTION-INFORMED DENOISING & RENDERING

    公开(公告)号:US20230065183A1

    公开(公告)日:2023-03-02

    申请号:US17520089

    申请日:2021-11-05

    Abstract: A graphics processor is provided that includes circuitry configured to receive, at an input block of a neural network model, a set of data including previous frame data, current frame data, velocity data, and jitter offset data. The neural network model is configured to generate a denoised, supersampled, and anti-aliased output image based on reliability metrics computed based on sample distribution data for samples within the current frame data.

    AUGMENTING MOTION VECTORS VIA PROCEDURAL SHADER OUTPUT

    公开(公告)号:US20230144562A1

    公开(公告)日:2023-05-11

    申请号:US17947262

    申请日:2022-09-19

    CPC classification number: G06T15/005 G06N3/10 G06T2200/12

    Abstract: A graphics processor is provided that includes circuitry configured to facilitate correspondence finding for higher-order light-based effects such as shadows, objects reflecting in mirrors, waves in water or other liquids, glossy surfaces, or objects visible through transparent and/or refractive glass. The circuitry is configured to procedurally generate temporally stable tracking data for transparent and reflective surfaces during rendering of successive frames, hierarchically analyze the successive frames to detect the procedurally generated data within the successive frames, generate residual motion vectors based on the hierarchical analysis, and warp and align a frame and a successively rendered frame based on renderer supplied motion vectors and the residual motion vectors.

    SAMPLING ACROSS MULTIPLE VIEWS IN SUPERSAMPLING OPERATION

    公开(公告)号:US20230146259A1

    公开(公告)日:2023-05-11

    申请号:US17980492

    申请日:2022-11-03

    CPC classification number: G06T3/4046 G06T3/4053 H04N13/271 G06T3/0093

    Abstract: Sampling across multiple views in supersampling operation is described. An example of an apparatus includes one or more processing resources configured to perform a supersampling operation for image data generated for multiple views utilizing one or more neural networks, the processing resources including at least a first circuitry to process a first current frame including first image data for a first view, and a second circuitry to process a second current frame including second image data for a second view, the first view and second view being displaced from each other, the processing resources to receive for processing the first current frame and the second current frame, and perform supersampling processing utilizing the one or more neural networks based on at least the first current frame and the second current frame and one or more prior generated frames for each of the views.

Patent Agency Ranking