- 专利标题: ATTRIBUTING GENERATED VISUAL CONTENT TO TRAINING EXAMPLES
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申请号: US17986347申请日: 2022-11-14
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公开(公告)号: US20240153039A1公开(公告)日: 2024-05-09
- 发明人: Yair ADATO , Ran ACHITUV , Eyal GUTFLAISH , Dvir YERUSHALMI
- 申请人: BRIA ARTIFICIAL INTELLIGENCE LTD
- 申请人地址: IL Tel Aviv
- 专利权人: BRIA ARTIFICIAL INTELLIGENCE LTD
- 当前专利权人: BRIA ARTIFICIAL INTELLIGENCE LTD
- 当前专利权人地址: IL Tel Aviv
- 主分类号: G06T5/50
- IPC分类号: G06T5/50 ; G06V10/772 ; G06V10/774
摘要:
Systems, methods and non-transitory computer readable media for attributing generated visual content to training examples are provided. A first visual content generated using a generative model may be received. The generative model may be associated with a plurality of training examples. Each training example may be associated with a visual content. Properties of the first visual content may be determined. Each visual content associated with a training example may be analyzed to determine properties of the visual content. The properties of the first visual content and the properties of the visual contents associated with the plurality of training examples may be used to attribute the first visual content to a subgroup of the plurality of training examples. The visual contents associated with the training examples of the subgroup may be associated with a source. A data-record associated with the source may be updated based on the attribution.
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