- 专利标题: 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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申请号: US15962735申请日: 2018-04-25
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公开(公告)号: US10783622B2公开(公告)日: 2020-09-22
- 发明人: Yilin Wang , Zhe Lin , Zhaowen Wang , Xin Lu , Xiaohui Shen , Chih-Yao Hsieh
- 申请人: Adobe Inc.
- 申请人地址: US CA San Jose
- 专利权人: ADOBE INC.
- 当前专利权人: ADOBE INC.
- 当前专利权人地址: US CA San Jose
- 代理机构: Keller Jolley Preece
- 主分类号: G06K9/00
- IPC分类号: G06K9/00 ; G06K9/62 ; G03B7/00 ; G06T5/50
摘要:
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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