- 专利标题: Attribute decorrelation techniques for image editing
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申请号: US17468476申请日: 2021-09-07
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公开(公告)号: US11875221B2公开(公告)日: 2024-01-16
- 发明人: Wei-An Lin , Baldo Faieta , Cameron Smith , Elya Shechtman , Jingwan Lu , Jun-Yan Zhu , Niloy Mitra , Ratheesh Kalarot , Richard Zhang , Shabnam Ghadar , Zhixin Shu
- 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: Kilpatrick Townsend & Stockton LLP
- 主分类号: G06N3/08
- IPC分类号: G06N3/08 ; G06F3/04845 ; G06F3/04847 ; G06T11/60 ; G06T3/40 ; G06N20/20 ; G06T5/00 ; G06T5/20 ; G06T3/00 ; G06T11/00 ; G06F18/40 ; G06F18/211 ; G06F18/214 ; G06F18/21 ; G06N3/045
摘要:
Systems and methods generate a filtering function for editing an image with reduced attribute correlation. An image editing system groups training data into bins according to a distribution of a target attribute. For each bin, the system samples a subset of the training data based on a pre-determined target distribution of a set of additional attributes in the training data. The system identifies a direction in the sampled training data corresponding to the distribution of the target attribute to generate a filtering vector for modifying the target attribute in an input image, obtains a latent space representation of an input image, applies the filtering vector to the latent space representation of the input image to generate a filtered latent space representation of the input image, and provides the filtered latent space representation as input to a neural network to generate an output image with a modification to the target attribute.
公开/授权文献
- US20220122232A1 ATTRIBUTE DECORRELATION TECHNIQUES FOR IMAGE EDITING 公开/授权日:2022-04-21
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