公开(公告)号：US20230326044A1

公开(公告)日：2023-10-12

申请号：US17714373

申请日：2022-04-06

Applicant: Adobe Inc.

Inventor： Simon Niklaus ,  Jiawen Chen

IPC: G06T7/269 ,  G06T11/00 ,  G06T3/40

CPC classification number: G06T7/269 ,  G06T11/00 ,  G06T3/40 ,  G06T2207/20221 ,  G06T2207/20084

Abstract: Digital image synthesis techniques are described that leverage splatting, i.e., forward warping. In one example, a first digital image and a first optical flow are received by a digital image synthesis system. A first splat metric and a first merge metric are constructed by the digital image synthesis system that defines a weighted map of respective pixels. From this, the digital image synthesis system produces a first warped optical flow and a first warp merge metric corresponding to an interpolation instant by forward warping the first optical flow based on the splat metric and the merge metric. A first warped digital image corresponding to the interpolation instant is formed by the digital image synthesis system by backward warping the first digital image based on the first warped optical flow.

公开(公告)号：US20240202989A1

公开(公告)日：2024-06-20

申请号：US18067878

申请日：2022-12-19

Applicant: Adobe Inc.

Inventor： Ethan Tseng ,  Zhihao Xia ,  Yifei Fan ,  Xuaner Zhang ,  Peter Merrill ,  Lars Jebe ,  Jiawen Chen

IPC: G06T11/00 ,  G06T11/60 ,  G06V10/77 ,  G06V10/774 ,  G06V10/82 ,  G06V20/40

CPC classification number: G06T11/001 ,  G06T11/60 ,  G06V10/7715 ,  G06V10/774 ,  G06V10/82 ,  G06V20/46 ,  G06V2201/10

Abstract: Digital content stylization techniques are described that leverage a neural photofinisher to generate stylized digital images. In one example, the neural photofinisher is implemented as part of a stylization system to train a neural network to perform digital image style transfer operations using reference digital content as training data. The training includes calculating a style loss term that identifies a particular visual style of the reference digital content. Once trained, the stylization system receives a digital image and generates a feature map of a scene depicted by the digital image. Based on the feature map as well as the style loss, the stylization system determines visual parameter values to apply to the digital image to incorporate a visual appearance of the particular visual style. The stylization system generates the stylized digital image by applying the visual parameter values to the digital image automatically and without user intervention.

公开(公告)号：US20240394834A1

公开(公告)日：2024-11-28

申请号：US18323233

申请日：2023-05-24

Applicant: Adobe Inc.

Inventor： Zhihao Xia ,  Michael Gharbi ,  Jiawen Chen ,  Goutam Bhat

IPC: G06T3/40 ,  G06T3/00 ,  G06T5/00 ,  G06T7/20 ,  G06V10/56

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that implements self-supervised training of an image burst model, trained exclusively on low-resolution images. For example, the disclosed system accesses an image burst that includes a plurality of images. The disclosed system generates a high-resolution image estimation from a first subset of images of the plurality of images. Further, the disclosed system generates a set of low-resolution images by modifying the high-resolution image estimation based on parameters of one or more images from the plurality of images. Moreover, the disclosed system determines a measure of loss by comparing the set of low-resolution images with a second subset of images from the plurality of images and updates the image burst model with the determined measure of loss.