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公开(公告)号：US20230130006A1
公开(公告)日：2023-04-27
申请号：US18145724
申请日：2022-12-22
Inventor： Dongliang HE , Errui DING , Haifeng WANG
IPC: G06V20/40 , G06V10/774 , G06V10/86 , G06F16/73 , G06F16/783
Abstract: The present application provides a method of processing a video, a method of querying a video, and a method of training a video processing model. A specific implementation solution of the method of processing the video includes: extracting, for a video to be processed, a plurality of video features under a plurality of receptive fields; extracting a local feature of the video to be processed according to a video feature under a target receptive field in the plurality of receptive fields; obtaining a global feature of the video to be processed according to a video feature under a largest receptive field in the plurality of receptive fields; and merging the local feature and the global feature to obtain a target feature of the video to be processed.
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2.发明申请公开(公告)号：US20230120253A1
公开(公告)日：2023-04-20
申请号：US18082997
申请日：2022-12-16
Inventor： Jie Li , Haojie LIU , Yan ZHANG , Xuecen SHEN , Ruizhi CHEN , Chen ZHAO , Yuqiao TENG , Errui DING , Tian WU , Haifeng WANG
Abstract: A method and apparatus for generating a virtual character, an electronic device and a computer readable storage medium are provided. The method includes: performing mesh simplification on an initial model of a virtual character to obtain a mesh-simplified model; obtaining a first target model by performing white model mapping rendering on an area of each material type on the mesh-simplified model, and obtaining a second target model by performing hyper-realistic rendering on the area of each material type on the mesh-simplified model; and establishing a bidirectional mapping between the first target model and the second target model, and obtaining a target virtual character through iterative updating of the bidirectional mapping.
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公开(公告)号：US20210192214A1
公开(公告)日：2021-06-24
申请号：US17164681
申请日：2021-02-01
Inventor： Minyue JIANG , Xiao TAN , Hao SUN , Hongwu ZHANG , Shilei WEN , Errui DING
Abstract: The present application discloses a vehicle re-identification method and apparatus, a device and a storage medium, which relates to the field of computer vision, intelligent search, deep learning and intelligent transportation. The specific implementation scheme is: receiving a re-identification request from a terminal device, the re-identification request including a first image of a first vehicle shot by a first camera and information of the first camera; acquiring a first feature of the first vehicle and a first head orientation of the first vehicle according to the first image; determining a second image of the first vehicle from images of multiple vehicles according to the first feature, multiple second features extracted based on the images of the multiple vehicles in an image database, the first head orientation of the first vehicle, and the information of the first camera; and transmitting the second image to the terminal device.
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4.发明公开公开(公告)号：US20230147550A1
公开(公告)日：2023-05-11
申请号：US18051594
申请日：2022-11-01
Inventor： Dongliang HE , Errui DING
IPC: G06V10/774 , G06V20/40 , G06F40/30 , G06V30/19
CPC classification number: G06V10/774 , G06V20/41 , G06F40/30 , G06V30/19147
Abstract: A method for pre-training a semantic representation model includes: for each video-text pair in pre-training data, determining a mask image sequence, a mask character sequence, and a mask image-character sequence of the video-text pair; determining a plurality of feature sequences and mask position prediction results respectively corresponding to the plurality of feature sequences by inputting the mask image sequence, the mask character sequence, and the mask image-character sequence into an initial semantic representation model; and building a loss function based on the plurality of feature sequences, the mask position prediction results respectively corresponding to the plurality of feature sequences and true mask position results, and adjusting coefficients of the semantic representation model to realize training.
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公开(公告)号：US20220392101A1
公开(公告)日：2022-12-08
申请号：US17887740
申请日：2022-08-15
Inventor： Zipeng LU , Jian WANG , Hao SUN , Errui DING
IPC: G06T7/70 , G06T7/62 , G06V10/25 , G06V10/74 , G06V10/774
Abstract: A training method, a method of detecting a target image, an electronic device and a medium, which relate to the field of artificial intelligence technology, and in particular to fields of computer vision and deep learning. The method can include: generating an expanded sample image set for a target scene by using a mask image set and an initial sample image set, wherein the mask image set is acquired by parsing a predetermined image set, a target object in the target scene is interfered by another object or the target object in the target scene is cut off, and an image in the predetermined image set includes the target object in the target scene or the another object; and training, by using the initial sample image set and the expanded sample image set, a detection model for detecting the target object.
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Patent Agency Ranking
公开(公告)号：US20220301131A1
公开(公告)日：2022-09-22
申请号：US17743057
申请日：2022-05-12
Inventor： Jingwei LIU , Yi GU , Xuhui LIU , Xiaodi WANG , Shumin HAN , Yuan FENG , Ying XIN , Chao LI , Bin ZHANG , Honghui ZHENG , Xiang LONG , Yan PENG , Errui DING , Yunhao WANG
Abstract: A method for generating a sample image includes: obtaining an initial image size of an initial image; obtaining a plurality of reference images by processing the initial image based on different reference processing modes; obtaining an image to be processed by fusing the plurality of reference images; and determining a target sample image from images to be processed based on the initial image size.
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公开(公告)号：US20220027611A1
公开(公告)日：2022-01-27
申请号：US17498226
申请日：2021-10-11
Inventor： Yuechen YU , Chengquan ZHANG , Yulin LI , Xiaoqiang ZHANG , Ju HUANG , Xiameng QIN , Kun YAO , Jingtuo LIU , Junyu HAN , Errui DING
Abstract: Provided are an image classification method and apparatus, an electronic device and a storage medium, relating to the field of artificial intelligence and, in particular, to computer vision and deep learning. The method includes inputting a to-be-classified document image into a pretrained neural network and obtaining a feature submap of each text box of the to-be-classified document image by use of the neural network; inputting the feature submap of each text box, a semantic feature corresponding to preobtained text information of each text box and a position feature corresponding to preobtained position information of each text box into a pretrained multimodal feature fusion model and fusing, by use of the multimodal feature fusion model, the three into a multimodal feature corresponding to each text box; and classifying the to-be-classified document image based on the multimodal feature corresponding to each text box.
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公开(公告)号：US20230027813A1
公开(公告)日：2023-01-26
申请号：US17936570
申请日：2022-09-29
Inventor： Xipeng YANG , Xiao TAN , Hao SUN , Errui DING
Abstract: An object detecting method includes: obtaining an object image of an object; obtaining an object feature map by performing feature extraction on the object image; obtaining decoded features by performing feature mapping on the object feature map by adopting a mapping network of an object recognition model; obtaining positions of prediction boxes by inputting the decoded features into a first prediction layer of the object recognition model to perform object regression prediction; and obtaining classes of objects within the prediction boxes by inputting the decoded features into a second prediction layer of the object recognition model to perform object class prediction.
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公开(公告)号：US20220392205A1
公开(公告)日：2022-12-08
申请号：US17892669
申请日：2022-08-22
Inventor： Yipeng SUN , Rongqiao AN , Xiang WEI , Longchao WANG , Kun YAO , Junyu HAN , Jingtuo LIU , Errui DING
Abstract: Embodiments of the present disclosure provide a method and apparatus for training an image recognition model based on a semantic enhancement, a method and apparatus for recognizing an image, an electronic device, and a computer readable storage medium. The method for training an image recognition model based on a semantic enhancement comprises: extracting, from an inputted first image being unannotated and having no textual description, a first feature representation of the first image; calculating a first loss function based on the first feature representation; extracting, from an inputted second image being unannotated and having an original textual description, a second feature representation of the second image; calculating a second loss function based on the second feature representation, and training an image recognition model based on a fusion of the first loss function and the second loss function.
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10.发明申请公开(公告)号：US20220139061A1
公开(公告)日：2022-05-05
申请号：US17576198
申请日：2022-01-14
Inventor： Jian WANG , Zipeng LU , Hao SUN , Zhiyong JIN , Errui DING
Abstract: Provided are a training method and apparatus for a human keypoint positioning model, a human keypoint positioning method and apparatus, a device, a medium and a program product. The training method includes determining an initial positioned point of each of keypoints; acquiring N candidate points of each keypoint according to a position of the initial positioned point; extracting a first feature image, and forming N sets of graph structure feature data according to the first feature image and the N candidate points; performing graph convolution on the N sets of graph structure feature data to obtain N sets of offsets; correcting initial positioned points of all the keypoints to obtain N sets of current positioning results; and calculating each set of loss values according to labeled true values of all the keypoints and each set of current positioning results, and performing supervised training on the positioning model.
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