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公开(公告)号：US20250166267A1
公开(公告)日：2025-05-22
申请号：US18949486
申请日：2024-11-15
Applicant: Lemon Inc.
Inventor： Song BAI , Yujun Shi , Chuhui Xue , Wenqing Zhang
Abstract: Embodiments of the disclosure relate to interactive point-based image editing. According to example embodiments of the present disclosure, a user edit input for a source image is obtained to indicate at least one handle point and at least one target point in the source image. A feature map is extracted from the source image using a diffusion model at an iteration step of an inverse denoising diffusion process performed on the source image. The feature map is then updated based on the user edit input. Then a target image is generated based on the updated feature map using the diffusion model through a denoising diffusion process performed on the updated feature map.
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公开(公告)号：US20240104894A1
公开(公告)日：2024-03-28
申请号：US17949078
申请日：2022-09-20
Applicant: Lemon Inc.
IPC: G06V10/764 , G06V10/72 , G06V10/771
CPC classification number: G06V10/764 , G06V10/72 , G06V10/771
Abstract: A method is proposed for sample processing. A first group of data are received, here data in the first group of data comprises a sample and a classification of the sample, and the classification belonging to a first group of classifications in a plurality of classifications associated with the data. A plurality of data with the classification are selected from the first group of data. A first and a second loss function are determined for training a classification model that represents an association relationship between samples and classifications of the samples based on a plurality of samples comprised in the plurality of data and the classification, the first and second loss functions represent classification accuracy and a feature distribution for the classification model. The classification model is trained based on the first and second loss functions. Therefore, the accuracy of the classification model may be increased.
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