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公开(公告)号：US20240303774A1
公开(公告)日：2024-09-12
申请号：US18020918
申请日：2022-06-10
Inventor： Changyong SHU , Jiaming LIU , Zhibin HONG , Junyu HAN
CPC classification number: G06T5/50 , G06T5/60 , G06T7/40 , G06T7/55 , G06T7/90 , G06V40/172 , G06T2207/10024 , G06T2207/20081 , G06T2207/20084 , G06T2207/20221 , G06T2207/30201
Abstract: A method of processing an image, an electronic device and a storage medium. The method includes: generating a to-be-processed image according to a first target image and a second target image, where an identity information of an object in the to-be-processed image is matched with an identity information of an object in the first target image; generating a set of disentangled images according to the second target image and the to-be-processed image, where the set of disentangled images includes a head-disentangled image and a disentangled repair image; and generating a fusion image according to the set of disentangled images, where an identity information and a texture information of an object in the fusion image are matched with the identity information and the texture information of the object in the to-be-processed image, respectively, and a to-be-repaired information related to the object in the fusion image is repaired.
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公开(公告)号：US20240331093A1
公开(公告)日：2024-10-03
申请号：US18020891
申请日：2022-06-09
Inventor： Zhiliang XU , Zhibin HONG
CPC classification number: G06T5/50 , G06V10/245 , G06T2207/20081 , G06T2207/20221
Abstract: A method of training a fusion model, a method of fusing an image, an electronic device, and a storage medium are provided, which relate to a field of an artificial intelligence technology, in particular to fields of computer vision and deep learning technologies, and may be applied to face image processing, face recognition and other scenarios. A specific implementation solution includes: inputting a training source image and a training template image into a fusion model to obtain a training fusion image; performing an attribute alignment transformation on the training fusion image to obtain a training aligned image, wherein an attribute information of the training aligned image is consistent with an attribute information of the training source image; and training the fusion model using an identity loss function, wherein the identity loss function is generated for the training source image and the training aligned image.
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公开(公告)号：US20230143452A1
公开(公告)日：2023-05-11
申请号：US17982832
申请日：2022-11-08
Inventor： Zhiliang XU , Zhibin HONG
CPC classification number: G06T7/55 , G06V10/40 , G06V10/24 , G06T2207/20221 , G06T2207/20084
Abstract: A method for generating an image includes: obtaining a reference image and an image to be processed; extracting target fusion features from the reference image; determining a plurality of depth feature maps corresponding to the reference image based on the target fusion features; obtaining a target feature map by fusing the plurality of depth feature maps based on the target fusion features; and generating a target image by processing the image to be processed based on the target feature map.
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公开(公告)号：US20220188637A1
公开(公告)日：2022-06-16
申请号：US17683512
申请日：2022-03-01
Inventor： Jiaming LIU , Licheng TANG , Zhibin HONG
IPC: G06N3/08 , G06N3/04 , G06F40/109
Abstract: There are provided a method for training an adversarial network model, a method for building a character library, an electronic device and a storage medium, which relate to a field of artificial intelligence technology, in particular to a field of computer vision and deep learning technologies. The method includes: generating a generated character based on a content character sample having a base font and a style character sample having a style font and generating a reconstructed character based on the content character sample, by using a generation model; calculating a basic loss of the generation model based on the generated character and the reconstructed character, by using a discrimination model; calculating a character loss of the generation model through classifying the generated character by using a trained character classification model; and adjusting a parameter of the generation model based on the basic loss and the character loss.
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公开(公告)号：US20220028143A1
公开(公告)日：2022-01-27
申请号：US17498249
申请日：2021-10-11
Inventor： Tianshu HU , Zhibin HONG
Abstract: Provided are a video generation method and apparatus, a device and a storage medium, relating to the field of artificial intelligence and, in particular, to the fields of computer vision and deep learning. The method includes changing a character emotion of an original character image according to a character emotion feature of a to-be-generated video to obtain a target character image; and driving the target character image by use of a character driving network and based on a speech segment to obtain the to-be-generated video.
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Patent Agency Ranking
6.发明申请公开(公告)号：US20230022550A1
公开(公告)日：2023-01-26
申请号：US17937979
申请日：2022-10-04
Inventor： Hanqi GUO , Zhibin HONG , Tianshu HU
Abstract: An image processing method includes: obtaining a first latent code by encoding an image to be edited in a Style (S) space of a Generative Adversarial Network (GAN), in which the GAN is a StyleGAN; encoding the text description information, obtaining a text code of a Contrastive Language-Image Pre-training (CLIP) model, and obtaining a second latent code by mapping the text code on the S space; obtaining a target latent code that satisfies distance requirements by performing distance optimization on the first latent code and the second latent code; and generating a target image based on the target latent code.
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公开(公告)号：US20220270384A1
公开(公告)日：2022-08-25
申请号：US17683945
申请日：2022-03-01
Inventor： Jiaming LIU , Zhibin HONG , Licheng TANG
Abstract: The present disclosure discloses a method for training an adversarial network model, a method for building a character library, an electronic device and a storage medium, which relate to a field of artificial intelligence, in particular to a field of computer vision and deep learning technologies, and are applicable in a scene of image processing and image recognition. The method for training includes: generating a new character by using the generation model based on a stroke character sample and a line character sample; discriminating a reality of the generated new character by using the discrimination model; calculating a basic loss based on the new character and a discrimination result; calculating a track consistency loss based on a track consistency between the line character sample and the new character; and adjusting a parameter of the generation model according to the basic loss and the track consistency loss.
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公开(公告)号：US20220005244A1
公开(公告)日：2022-01-06
申请号：US17479056
申请日：2021-09-20
Inventor： Zhizhi GUO , Borong LIANG , Zhibin HONG , Junyu HAN
Abstract: The present disclosure relates to a field of artificial intelligence technology, in particular to a field of computer vision and deep learning technology, and more particularly, a method and an apparatus for changing a hairstyle of a character, a device, and a storage medium are provided. The method includes: determining an original feature vector of an original image containing the character, wherein the character in the original image has an original hairstyle; acquiring a boundary vector associated with the original hairstyle and a target hairstyle based on a hairstyle classification model; determining a target feature vector corresponding to the target hairstyle based on the original feature vector and the boundary vector; and generating a target image containing the character based on the target feature vector, wherein the character in the target image has the target hairstyle.
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公开(公告)号：US20230145443A1
公开(公告)日：2023-05-11
申请号：US17959727
申请日：2022-10-04
Inventor： Tianshu HU , Hanqi GUO , Junyu HAN , Zhibin HONG
IPC: G06T3/40
CPC classification number: G06T3/4038
Abstract: Provided are a video stitching method and an apparatus, an electronic device, and a storage medium. In the video stitching method, an intermediate frame is inserted between a last image frame of a first video and a first image frame of a second video. L image frames are sequentially selected in order from back to front from the first video and L image frames are sequentially selected in order from front to back from the second video separately, and L is a natural number greater than 1. The first video and the second video are stitched together to form a target video according to the intermediate frame, the L image frames in the first video, and the L image frames in the second video.
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10.发明申请公开(公告)号：US20220383574A1
公开(公告)日：2022-12-01
申请号：US17883037
申请日：2022-08-08
Inventor： Zhanwang ZHANG , Tianshu HU , Zhibin HONG , Zhiliang XU
Abstract: A virtual object lip driving method performed by an electronic device includes: obtaining a speech segment and target face image data about a virtual object; and inputting the speech segment and the target face image data into a first target model to perform a first lip driving operation, so as to obtain first lip image data about the virtual object driven by the speech segment. The first target model is trained in accordance with a first model and a second model, the first model is a lip-speech synchronization discriminative model with respect to lip image data, and the second model is a lip-speech synchronization discriminative model with respect to a lip region in the lip image data.
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