Invention Grant
- Patent Title: Training and utilizing an image exposure transformation neural network to generate a long-exposure image from a single short-exposure image
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Application No.: US15962735Application Date: 2018-04-25
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Publication No.: US10783622B2Publication Date: 2020-09-22
- Inventor: Yilin Wang , Zhe Lin , Zhaowen Wang , Xin Lu , Xiaohui Shen , Chih-Yao Hsieh
- Applicant: Adobe Inc.
- Applicant Address: US CA San Jose
- Assignee: ADOBE INC.
- Current Assignee: ADOBE INC.
- Current Assignee Address: US CA San Jose
- Agency: Keller Jolley Preece
- Main IPC: G06K9/00
- IPC: G06K9/00 ; G06K9/62 ; G03B7/00 ; G06T5/50

Abstract:
The present disclosure relates to training and utilizing an image exposure transformation network to generate a long-exposure image from a single short-exposure image (e.g., still image). In various embodiments, the image exposure transformation network is trained using adversarial learning, long-exposure ground truth images, and a multi-term loss function. In some embodiments, the image exposure transformation network includes an optical flow prediction network and/or an appearance guided attention network. Trained embodiments of the image exposure transformation network generate realistic long-exposure images from single short-exposure images without additional information.
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