Invention Application
- Patent Title: TRANSFERRING HAIRSTYLES BETWEEN PORTRAIT IMAGES UTILIZING DEEP LATENT REPRESENTATIONS
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Application No.: US17034845Application Date: 2020-09-28
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Publication No.: US20220101577A1Publication Date: 2022-03-31
- Inventor: Saikat Chakrabarty , Sunil Kumar
- Applicant: Adobe Inc.
- Applicant Address: US CA San Jose
- Assignee: Adobe Inc.
- Current Assignee: Adobe Inc.
- Current Assignee Address: US CA San Jose
- Main IPC: G06T11/60
- IPC: G06T11/60 ; G06K9/00 ; G06T5/50 ; G06N3/08

Abstract:
The disclosure describes one or more embodiments of systems, methods, and non-transitory computer-readable media that generate a transferred hairstyle image that depicts a person from a source image having a hairstyle from a target image. For example, the disclosed systems utilize a face-generative neural network to project the source and target images into latent vectors. In addition, in some embodiments, the disclosed systems quantify (or identify) activation values that control hair features for the projected latent vectors of the target and source image. Furthermore, in some instances, the disclosed systems selectively combine (e.g., via splicing) the projected latent vectors of the target and source image to generate a hairstyle-transfer latent vector by using the quantified activation values. Then, in one or more embodiments, the disclosed systems generate a transferred hairstyle image that depicts the person from the source image having the hairstyle from the target image by synthesizing the hairstyle-transfer latent vector.
Public/Granted literature
- US11790581B2 Transferring hairstyles between portrait images utilizing deep latent representations Public/Granted day:2023-10-17
Information query