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公开(公告)号：US20250124679A1
公开(公告)日：2025-04-17
申请号：US18748082
申请日：2024-06-19
Inventor： Lei WANG , Xiaodong ZHANG , Shiyan LI
Abstract: The present disclosure provides method and apparatus for transferring facial expression of digital human, electronic device, and storage medium, which relates to the fields of augmented reality technologies, virtual reality technologies, computer vision technologies, deep learning technologies, or the like, and can be applied to scenarios, such as metaverse, a virtual digital human, or the like, An implementation includes: screening an identification of a target reference model matched with an object model from a preset reference model library; the reference model library including a plurality of reference models; acquiring an expression library of the target reference model based on the identification of the target reference model; and transferring a last frame of an expression in the expression library of the target reference model into the object model to obtain a last frame of an expression of the object model.
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公开(公告)号：US20250078305A1
公开(公告)日：2025-03-06
申请号：US18043705
申请日：2022-06-20
Inventor： Lei WANG , Ying WANG , Xiaoting ZANG
IPC: G06T7/70
Abstract: The present disclosure provides a data marking method, apparatus, system, device, and storage medium, and relates to the technical field of data processing, and in particular to fields such as artificial intelligence, big data, and deep learning. The specific implementation solution is as follows: acquiring multiple pictures whose contents are continuous, wherein the multiple pictures contain at least one same object; for each object, determining a position offset of the object by using position information of the object in two adjacent pictures, wherein the two adjacent pictures include a first previous picture and a second previous picture, the second previous picture is a picture before and adjacent to a picture to be marked in time sequence; the first previous picture is a picture before and adjacent to the second previous picture in time sequence; determining estimated position information of the object in the picture to be marked based on the position information of the second previous picture and the position offset; marking the object in the picture to be marked based on the estimated position information. The present disclosure can speed up the marking of the same object in multiple pictures.
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公开(公告)号：US20250124651A1
公开(公告)日：2025-04-17
申请号：US18748080
申请日：2024-06-19
Inventor： Yichen LI , Lei WANG , Xiaodong ZHANG , Shiyan LI
IPC: G06T17/00
Abstract: The present disclosure provides method and apparatus for generating 3D scene based on large language model, electronic device, and storage medium, which relates to the field of artificial intelligence technologies, particularly the fields of three-dimensional modeling technologies, large language model technologies, or the like. The three-dimensional scene generating method based on a large language model includes: processing description information of a target three-dimensional scene to obtain label information in the description information; generating query operation prompt of the LLM based on the label information, and acquiring a target asset set matched with the label information by the LLM based on the query operation prompt, the target asset set including a target asset in the target three-dimensional scene, target material information of the target asset and target scene attribute information of the target asset; and generating the target three-dimensional scene based on the target asset set.
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Patent Agency Ranking
公开(公告)号：US20240095141A1
公开(公告)日：2024-03-21
申请号：US18025148
申请日：2022-03-21
Inventor： Yifan ZHANG , Yuqi WANG , Linfei CHU , Jing NING , Kunjie SUN , Yuhang ZHENG , Naifei SONG , Shujuan ZHANG , Lin LIU , Xunzhuo JU , Zhengwei CHEN , Wei ZHANG , Hua ZHANG , Congjun ZHOU , Tingkang WU , Tengfei LV , Hanmeng LIU , Lei WANG
IPC: G06F11/32 , G06F3/0483
CPC classification number: G06F11/323 , G06F3/0483
Abstract: A method and an apparatus for displaying an information flow on a terminal device, an electronic device, a computer-readable storage medium, and a computer program product are provided. An implementation is: in response to detecting an activation operation on an application for displaying the information flow, reproducing, on the terminal device, a first page displayed on the terminal device when the application is last switched to running in the background or closed; and in response to determining that a time interval between the activation operation and the application being last switched to running in the background or closed does not exceed a first threshold, displaying a second page as a continuation of a content entry displayed in the first page, where the second page includes at least one first content entry cached in the terminal device before the activation operation but not displayed in the first page.
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公开(公告)号：US20230305882A1
公开(公告)日：2023-09-28
申请号：US17942696
申请日：2022-09-12
Inventor： Tianfei WANG , Buhe HAN , Zhen CHEN , Lei WANG
IPC: G06F9/48
CPC classification number: G06F9/4812
Abstract: Provided are a method for processing data, an electronic device and a storage medium, which relate to the field of deep learning and data processing. The method may include: multiple target operators of a target model are acquired; the multiple target operators are divided into at least one operator group, according to an operation sequence of each of the multiple target operators in the target model, wherein at least one target operator in each of the at least one operator group is operated by the same processor and is operated within the same target operation period; and the at least one operator group is output.
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公开(公告)号：US20250124680A1
公开(公告)日：2025-04-17
申请号：US18748083
申请日：2024-06-19
Inventor： Lei WANG , Xiaodong ZHANG , Shiyan LI
Abstract: A digital human generation method, an electronic device and a storage medium are disclosed. The solution relates to the fields of augmented reality technologies, virtual reality technologies, computer vision technologies, deep learning technologies, or the like, and can be applied to scenarios, such as metaverse, a virtual digital human, or the like. An implementation includes: acquiring a corresponding target object model based on a picture of a to-be-generated digital human; acquiring a corresponding point cloud of a head key feature in the picture from a pre-configured feature library based on the head key feature; and fusing the point cloud of the head key feature in the target object model to obtain a digital human figure.
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7.发明公开公开(公告)号：US20230195839A1
公开(公告)日：2023-06-22
申请号：US17555723
申请日：2021-12-20
Inventor： Binghong WU , Yehui YANG , DaLU YANG , Yanwu XU , Lei WANG , Qian LI
IPC: G06K9/62
CPC classification number: G06K9/6257 , G06K9/6232 , G06K9/6201
Abstract: Technical solutions relate to the field of artificial intelligence such as deep learning, computer vision and intelligent imaging. A method may includes during training of a one-stage object detecting model, acquiring values of a loss function corresponding to feature maps at different scales respectively in the case that classification loss calculation is required, and the loss function is a focal loss function; and determining a final value of the loss function according to the acquired values of the loss function, and training the one-stage object detecting model according to the final value of the loss function.
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公开(公告)号：US20210192728A1
公开(公告)日：2021-06-24
申请号：US17097632
申请日：2020-11-13
Inventor： Fangxin SHANG , Yehui YANG , Lei WANG , Yanwu XU
Abstract: The present application discloses an image processing method, an apparatus, an electronic device and a storage medium. A specific implementation is: acquiring an image to be processed; acquiring a grading array according to the image to be processed and a grading network model, where the grading network model is a model pre-trained according to mixed samples, the number of elements contained in the grading array is C−1, C is the number of lesion grades, C lesion grades include one lesion grade without lesion and C−1 lesion grades with lesion, and a kth element in the grading array is a probability of a lesion grade corresponding to the image to be processed being greater than or equal to a kth lesion grade, where 1≤k≤C−1, and k is an integer; determining the lesion grade corresponding to the image to be processed according to the grading array.
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