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公开(公告)号:US20240104810A1
公开(公告)日:2024-03-28
申请号:US18257158
申请日:2021-11-22
Applicant: Lemon Inc.
Inventor: Xiao YANG , Jianwei LI , Ding LIU , Yangyue WAN , Xiaohui SHEN , Jianchao YANG
CPC classification number: G06T11/60 , G06T5/70 , G06T5/77 , G06T7/12 , G06V10/25 , G06V10/56 , G06T2207/10024
Abstract: Embodiments of the disclosure provide a method and a device for processing a portrait image, the method includes: acquiring a to-be-processed portrait image; inputting the to-be-processed portrait image into an image processing model, and acquiring a head smear image output by the image processing model, where the image processing model is configured to smear a hair area of a portrait located above a preset boundary in the portrait image, and the image processing model is generated by training a sample data set of a sample portrait image and a sample head smear image corresponding to the sample portrait image; rendering the head smear image with a head effect material to obtain a portrait image added with an effect; and displaying the portrait image added with the effect.
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公开(公告)号:US20230237764A1
公开(公告)日:2023-07-27
申请号:US17581423
申请日:2022-01-21
Applicant: Lemon Inc.
Inventor: Linjie YANG , Yiming CUI , Ding LIU
CPC classification number: G06V10/513 , G06V10/764 , G06T7/70 , G06V10/94 , G06V10/87 , G06V10/82 , G06T2207/30242 , G06T2207/20081 , G06T2207/20084
Abstract: Described are examples for detecting objects in an image on a device including setting, based on a condition, a number of sparse proposals to use in performing object detection in the image, performing object detection in the image based on providing the sparse proposals as input to an object detection process to infer object location and classification of one or more objects in the image, and indicating, to an application and based on an output of the object detection process, the object location and classification of the one or more objects.
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公开(公告)号:US20250097545A1
公开(公告)日:2025-03-20
申请号:US18711530
申请日:2022-11-18
Applicant: Lemon Inc.
Inventor: Weibo GONG , Xiaojie JIN , Ding LIU , Xiaohui SHEN
Abstract: The embodiments of the present disclosure provide a video generation method, an apparatus, a device, and a storage medium, the video generation method including: obtaining a plurality of images and music matched to the plurality of images; determining first feature information for the plurality of images and second feature information for the music; according to the first feature information, the second feature information and a plurality of pre-stored rendering effects, determining a target rendering effect combination; the rendering effects being animation, special effects or a transition; and generating a video according to the plurality of images, the music and the target rendering effect combination.
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公开(公告)号:US20240241907A1
公开(公告)日:2024-07-18
申请号:US18570310
申请日:2022-05-10
Applicant: LEMON INC.
Inventor: Ding LIU , Xiaojie JIN , Yan WANG , Weibo GONG
IPC: G06F16/68 , G06F16/55 , G06F16/65 , G06V10/764
CPC classification number: G06F16/68 , G06F16/55 , G06F16/65 , G06V10/764
Abstract: Embodiments of the disclosure provide a method, device, storage medium and program product for music screening. The method includes: obtaining at least one image and at least one piece of to-be-selected music; determining an analysis result of the at least one image corresponding to an image classification tag based on N predetermined image classification tags, N being an integer greater than or equal to 1; determining attribute information for each piece of to-be-selected music based on the at least one image and the at least one piece of to-be-selected music; determining target music that matches the at least one image among the at least one piece of to-be-selected music based on the analysis result and the attribute information of each piece of to-be-selected music.
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公开(公告)号:US20230252605A1
公开(公告)日:2023-08-10
申请号:US17669072
申请日:2022-02-10
Applicant: Lemon Inc.
Inventor: Ding LIU
CPC classification number: G06T5/002 , G06T5/20 , G06T5/50 , G06T2207/20016 , G06T2207/20024 , G06T2207/20084 , G06T2207/20081
Abstract: Example aspects include techniques for implementing a high-frequency attention network for single image super-resolution. These techniques may include extracting a plurality of features from an original image input into a CNN to generate a feature map, and restoring one or more high-frequency details of the original image via an efficient residual block (ERB) and a high-frequency attention block (HFAB) configured to assign a scaling factor to one or more high-frequency areas. In addition, the techniques may include generating reconstruction input information by performing an element-wise operation on the one or more high-frequency details and cross-connection information from the feature map and performing, by the CNN, an enhancement operation on the reconstruction input information to generate an enhanced image.
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