Invention Grant
- Patent Title: Image enhancement via iterative refinement based on machine learning models
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Application No.: US17391150Application Date: 2021-08-02
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Publication No.: US11769228B2Publication Date: 2023-09-26
- Inventor: Chitwan Saharia , Jonathan Ho , William Chan , Tim Salimans , David Fleet , Mohammad Norouzi
- Applicant: Google LLC
- Applicant Address: US CA Mountain View
- Assignee: Google LLC
- Current Assignee: Google LLC
- Current Assignee Address: US CA Mountain View
- Agency: McDonnell Boehnen Hulbert & Berghoff LLP
- Main IPC: G06T5/00
- IPC: G06T5/00 ; G06T5/50 ; G06T3/40 ; G06N3/08 ; G06N3/045

Abstract:
A method includes receiving, by a computing device, training data comprising a plurality of pairs of images, wherein each pair comprises an image and at least one corresponding target version of the image. The method also includes training a neural network based on the training data to predict an enhanced version of an input image, wherein the training of the neural network comprises applying a forward Gaussian diffusion process that adds Gaussian noise to the at least one corresponding target version of each of the plurality of pairs of images to enable iterative denoising of the input image, wherein the iterative denoising is based on a reverse Markov chain associated with the forward Gaussian diffusion process. The method additionally includes outputting the trained neural network.
Public/Granted literature
- US20230067841A1 Image Enhancement via Iterative Refinement based on Machine Learning Models Public/Granted day:2023-03-02
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