SAMPLE DISTRIBUTION-INFORMED DENOISING & RENDERING

SAMPLE DISTRIBUTION-INFORMED DENOISING & RENDERING

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, supersam...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Zirr, Tobias, Kim, SungYe
Format: Patent
Sprache:eng ; fre ; ger
Schlagworte:
CALCULATING
COMPUTING
COUNTING
IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
PHYSICS
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Beschreibung
Zusammenfassung: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.