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公开(公告)号：US20250131613A1
公开(公告)日：2025-04-24
申请号：US18834154
申请日：2022-12-15
Applicant: Lemon Inc.
Inventor： Yizhe ZHU , Bingchen LIU , Xiao YANG
Abstract: Provided in the embodiments of the present disclosure are a video generation method, and a training method for a video generation model. The video generation method includes: acquiring a first video, wherein the first video includes a first object image; and inputting the first video into a pre-trained video generation model to obtain a second video, wherein the video generation model is obtained by means of performing training on the basis of a target image and a plurality of sample image pairs obtained from a plurality of first sample images, an object image in the second video is generated on the basis of a preset animal image in the target image and the first object image, and a background image of the second video is generated on the basis of a first background image of the first video.
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2.发明公开公开(公告)号：US20240153153A1
公开(公告)日：2024-05-09
申请号：US18052870
申请日：2022-11-04
Applicant: Lemon Inc.
Inventor： Bingchen LIU , Yizhe ZHU , Xiao YANG
Abstract: Systems and methods are provided that include a processor executing a program to receive an input from a user, where the input including a first input text and a second input text. The processor is further configured to provide an initial image and, for a predetermined number of iterations, define a first and second regions of the initial image associated with the first and second input texts, respectively, define a plurality of patches of the initial image, input the initial image into a diffusion process to generate a processed image, back-propagate the processed image through a text-image match gradient calculator by generating an image embedding based on the processed image, generating a text embedding based on the region and the input text that are associated with a patch, and calculating a differential between the image embedding and the text embedding.
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公开(公告)号：US20240153152A1
公开(公告)日：2024-05-09
申请号：US18052866
申请日：2022-11-04
Applicant: Lemon Inc.
Inventor： Bingchen LIU , Yizhe ZHU , Xiao YANG
Abstract: Systems and methods are provided that include a processor executing a program to receive input text from a user. The processor is further configured to, for a predetermined number of iterations, input an initial image into a diffusion process to generate a processed image, back-propagate the processed image through a text-image match gradient calculator to calculate a gradient against the input text, and update the initial image with an image generated by applying the calculated gradient to the processed image. The pixel values of the processed image during a first portion of the predetermined number of iterations are value clamped to a first range, and pixel values of the processed image during a second portion of the predetermined number of iterations are value clamped to a second range that is a subset of the first range.
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公开(公告)号：US20250086758A1
公开(公告)日：2025-03-13
申请号：US18728042
申请日：2023-01-13
Applicant: Lemon Inc.
Inventor： Yichun SHI , Xiao YANG , Xiaohui SHEN
Abstract: The present disclosure provides an image processing method and device. The image processing method includes: performing, by an encoder and a first model, multiple iterations on an initial image to obtain a target image feature corresponding to the initial image; and performing, by a second model, image reconstruction based on the target image feature to obtain a reconstructed image of the initial image, both of the first model and the second model being neural networks for image reconstruction, wherein in the multiple iterations, an image feature extracted by the first model in the image reconstruction and an output image of the first model are feedback information for the encoder to assist the encoder in encoding the initial image.
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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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Patent Agency Ranking
公开(公告)号：US20230328197A1
公开(公告)日：2023-10-12
申请号：US18332243
申请日：2023-06-09
Applicant: Lemon Inc.
Inventor： Yaxi GAO , Chenyu SUN , Xiao YANG , Zhili CHEN , Linjie LUO , Jing LIU , Hengkai GUO , Huaxia LI , Hwankyoo Shawn KIM , Jianchao YANG
IPC: G06T7/73 , G06T7/12 , G11B27/036 , H04N5/265 , G11B27/10
CPC classification number: H04N5/265 , G06T7/12 , G06T7/73 , G11B27/036 , G11B27/10 , G06T2200/24 , G06T2207/10021 , G06T2207/20101
Abstract: Embodiments of the present disclosure provide a display method and apparatus based on augmented reality, a device, and a storage medium, the method includes receiving a first video; acquiring a video material by segmenting a target object from the first video; acquiring and displaying a real scene image, where the real scene image is acquired by an image collection apparatus; and displaying the video material at a target position of the real scene image in an augmented manner and playing the video material. Since the video material is acquired by receiving the first video and segmenting the target object from the first video, the video material may be set according to the needs of the user.
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公开(公告)号：US20240153194A1
公开(公告)日：2024-05-09
申请号：US18052865
申请日：2022-11-04
Applicant: Lemon Inc.
Inventor： Bingchen LIU , Yizhe ZHU , Xiao YANG
IPC: G06T15/02 , G06F40/289 , G06T5/00
CPC classification number: G06T15/02 , G06F40/289 , G06T5/002 , G06T2207/20081
Abstract: Systems and methods are provided that include a processor executing a program to match sentences from a sentence dataset with artistic phrases from an artistic phrase dataset to generate a plurality of safe phrases. The processor is further configured to, for each of the safe phrases, generate a safe image by, for a predetermined number of iterations, performing steps to input an initial image into a diffusion process to generate a processed image, wherein the diffusion process includes a first diffusion model, back-propagate the processed image through a text-image match gradient calculator to calculate a gradient against the safe phrase, and update the initial image by applying the gradient to the processed image. The processor is further configured to pair each of the generated safe images with their respective safe phrase to form a plurality of safe phrase-image pairs.
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8.发明公开公开(公告)号：US20240153151A1
公开(公告)日：2024-05-09
申请号：US18052862
申请日：2022-11-04
Applicant: Lemon Inc.
Inventor： Qing YAN , Bingchen LIU , Yizhe ZHU , Xiao YANG
Abstract: Systems and methods are provided that include a processor executing a program to process an initial image through a first diffusion stage to generate a final first stage image, wherein the first diffusion stage includes using a diffusion model, a gradient estimator model smaller than the diffusion model, and a text-image match gradient calculator. The processor further executes the program to process the final first stage image through a second diffusion stage to generate a final second stage image. The second diffusion stage includes, for a second predetermined number of iterations, inputting the final first stage image to through the diffusion model, back-propagate the image through the text-image match gradient calculator to calculate a second stage gradient against the input text, and update the final first stage image by applying the second stage gradient to the final first stage image.
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9.发明公开公开(公告)号：US20230306694A1
公开(公告)日：2023-09-28
申请号：US18020852
申请日：2021-08-26
Applicant: Lemon Inc.
Inventor： Jingcong ZHANG , Weikai LI , Zihao CHEN , Guohui WANG , Xiao YANG , Haiying CHENG , Anda LI , Ray MCCLURE , Zhili CHEN , Yiheng ZHU , Shihkuang CHU , Liyou XU , Yunzhu LI , Jianchao YANG
IPC: G06T19/00
CPC classification number: G06T19/006
Abstract: A list information display method and apparatus, an electronic device, and a storage medium are provided, the method includes: displaying list information in response to an information display operation triggered by a user; obtaining a real scene shooting image; and loading a plurality of types of information related to the list information into the real scene shooting image and display the real scene shooting image. Due to the use of virtual enhanced display technology, while the list information is displayed in the real scene shooting image, the plurality of types of information related to the list information are also displayed. On one hand, the user can obtain more information related to the list information while obtaining the list information, which improves the efficiency of information acquisition; and on the other hand, the user can obtain information in the real scene shooting image, which improves the visual effect and interactive experience.
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10.发明申请公开(公告)号：US20250078570A1
公开(公告)日：2025-03-06
申请号：US18726709
申请日：2023-01-04
Applicant: Lemon Inc.
Inventor： Yizhe ZHU , Xiao YANG , Jianwei LI , Xiaohui SHEN
Abstract: The present disclosure provides an expression driving method and apparatus, and a training method and apparatus of an expression driving model. The expression driving method includes acquiring a first video; and inputting the first video into a pre-trained expression driving model to obtain a second video. The expression driving model is trained based on a target sample image and a plurality of first sample images. A facial image in the second video is generated based on the target sample image. A gesture expression feature of the facial image in the second video is the same as a gesture expression feature of a facial image in the first video.
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