- 专利标题: Deep Saliency Prior
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申请号: US17856370申请日: 2022-07-01
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公开(公告)号: US20230015117A1公开(公告)日: 2023-01-19
- 发明人: Kfir Aberman , David Edward Jacobs , Kai Jochen Kohlhoff , Michael Rubinstein , Yossi Gandelsman , Junfeng He , Inbar Mosseri , Yael Pritch Knaan
- 申请人: Google LLC
- 申请人地址: US CA Mountain View
- 专利权人: Google LLC
- 当前专利权人: Google LLC
- 当前专利权人地址: US CA Mountain View
- 主分类号: G06T7/194
- IPC分类号: G06T7/194 ; G06V40/20 ; G06T7/11 ; G06T3/00 ; G06T11/00
摘要:
Techniques for tuning an image editing operator for reducing a distractor in raw image data are presented herein. The image editing operator can access the raw image data and a mask. The mask can indicate a region of interest associated with the raw image data. The image editing operator can process the raw image data and the mask to generate processed image data. Additionally, a trained saliency model can process at least the processed image data within the region of interest to generate a saliency map that provides saliency values. Moreover, a saliency loss function can compare the saliency values provided by the saliency map for the processed image data within the region of interest to one or more target saliency values. Subsequently, the one or more parameter values of the image editing operator can be modified based at least in part on the saliency loss function.
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