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公开(公告)号：US20240281609A1
公开(公告)日：2024-08-22
申请号：US18041207
申请日：2022-05-16
Inventor： Pengyuan LV , Jingquan LI , Chengquan ZHANG , Kun YAO , Jingtuo LIU , Junyu HAN
Abstract: The present application provides a method of training a text recognition model. The method includes: inputting a first sample image into the visual feature extraction sub-model to obtain a first visual feature and a first predicted text, the first sample image contains a text and a tag indicating a first actual text; obtaining, by using the semantic feature extraction sub-model, a first semantic feature based on the first predicted text; obtaining, by using the sequence sub-model, a second predicted text based on the first visual feature and the first semantic feature; and training the text recognition model based on the first predicted text, the second predicted text and the first actual text. The present disclosure further provides a method of recognizing a text, an electronic device, and a storage medium.
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公开(公告)号：US20230186664A1
公开(公告)日：2023-06-15
申请号：US18169032
申请日：2023-02-14
Inventor： Shanshan LIU , Meina QIAO , Liang WU , Pengyuan LV , Sen FAN , Chengquan ZHANG , Kun YAO
CPC classification number: G06V30/19173 , G06V30/19147 , G06V30/30
Abstract: A method for text recognition is disclosed. The method includes obtaining a whole-image scenario for an image to be processed and a text image in the image to be processed. The method further includes determining a first text recognition model corresponding to the whole-image scenario. The method further includes performing text recognition on the text image according to the first text recognition model to obtain text information.
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公开(公告)号：US20230050079A1
公开(公告)日：2023-02-16
申请号：US17974630
申请日：2022-10-27
Inventor： Pengyuan LV , Xiaoyan WANG , Liang WU , Shanshan LIU , Yuechen YU , Meina QIAO , Jie LU , Chengquan ZHANG , Kun YAO
IPC: G06V30/18 , G06V30/148
Abstract: Provided are a text recognition method, an electronic device, and a non-transitory computer-readable storage medium, which are applicable in an OCR scenario. In the particular solution, a text image to be recognized is acquired. Feature extraction is performed on the text image, to obtain an image feature corresponding to the text image, where a height-wise feature and a width-wise feature of the image feature each have a dimension greater than 1. According to the image feature, sampling features corresponding to multiple sampling points in the text image are determined. According to the sampling features corresponding to the multiple sampling points, a character recognition result corresponding to the text image is determined.
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公开(公告)号：US20210406619A1
公开(公告)日：2021-12-30
申请号：US17169112
申请日：2021-02-05
Inventor： Pengyuan LV , Xiaoqiang ZHANG , Shanshan LIU , Chengquan ZHANG , Qiming PENG , Sijin WU , Hua LU , Yongfeng CHEN
IPC: G06K9/72 , G06T7/70 , G06F40/30 , G06K9/46 , G06K9/00 , G06K9/32 , G06K9/20 , G06K9/62 , G06N20/00 , G06N5/04
Abstract: The present disclosure provides a method for visual question answering, which relates to fields of computer vision and natural language processing. The method includes: acquiring an input image and an input question; detecting visual information and position information of each of at least one text region in the input image; determining semantic information and attribute information of each of the at least one text region based on the visual information and the position information; determining a global feature of the input image based on the visual information, the position information, the semantic information, and the attribute information; determining a question feature based on the input question; and generating a predicted answer for the input image and the input question based on the global feature and the question feature. The present disclosure further provides a device for visual question answering, a computer device and a medium.
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Patent Agency Ranking
公开(公告)号：US20240304015A1
公开(公告)日：2024-09-12
申请号：US18041265
申请日：2022-04-21
Inventor： Sen FAN , Xiaoyan WANG , Pengyuan LV , Chengquan ZHANG , Kun YAO
IPC: G06V30/19 , G06V30/148 , G06V30/18
CPC classification number: G06V30/19167 , G06V30/153 , G06V30/18 , G06V30/19147 , G06V30/1916
Abstract: The present disclosure provides a method of training a deep learning model for text detection and a text detection method, which relates to the technical field of artificial intelligence, and in particular, to the technical field of computer vision and deep learning and can be used in scenarios of OCR optical character recognition. A method of training a deep learning model for text detection is provided, in which a single character segmentation sub-network outputs a single character segmentation prediction result, a text line segmentation sub-network outputs a text line segmentation prediction result, the trained deep learning model can be used for detecting a text area; and, can at the same time achieve single character segmentation and text line segmentation, and thus is capable to perform text detection by combining two ways of text segmentation, which further improves the accuracy of text area detection.
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公开(公告)号：US20230045715A1
公开(公告)日：2023-02-09
申请号：US17966112
申请日：2022-10-14
Inventor： Chengquan ZHANG , Pengyuan LV , Sen FAN , Kun YAO , Junyu HAN , Jingtuo LIU
Abstract: The present disclosure provides a text detection method, a text recognition method and an apparatus, which relate to the field of artificial intelligence technology, in particular to the field of deep learning and computer vision technologies, and can be applied to scenarios such as optical character recognition. The text detection method is: acquiring an image feature of a text strip in a to-be-recognized image; performing visual enhancement processing on the to-be-recognized image to obtain an enhanced feature map of the to-be-recognized image; comparing the image feature of the text strip with the enhanced feature map for similarity to obtain a target bounding box of the text strip on the enhanced feature map.
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公开(公告)号：US20230215203A1
公开(公告)日：2023-07-06
申请号：US18168759
申请日：2023-02-14
Inventor： Pengyuan LV , Chengquan ZHANG , Shanshan LIU , Meina QIAO , Yangliu XU , Liang WU , Xiaoyan WANG , Kun YAO , Junyu Han , Errui DING , Jingdong WANG , Tian WU , Haifeng WANG
IPC: G06V30/19
CPC classification number: G06V30/19147 , G06V30/19167
Abstract: The present disclosure provides a character recognition model training method and apparatus, a character recognition method and apparatus, a device and a medium, relating to the technical field of artificial intelligence, and specifically to the technical fields of deep learning, image processing and computer vision, which can be applied to scenarios such as character detection and recognition technology. The specific implementing solution is: partitioning an untagged training sample into at least two sub-sample images; dividing the at least two sub-sample images into a first training set and a second training set; where the first training set includes a first sub-sample image with a visible attribute, and the second training set includes a second sub-sample image with an invisible attribute; performing self-supervised training on a to-be-trained encoder by taking the second training set as a tag of the first training set, to obtain a target encoder.
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公开(公告)号：US20230206667A1
公开(公告)日：2023-06-29
申请号：US18147806
申请日：2022-12-29
Inventor： Pengyuan LV , Liang WU , Shanshan LIU , Meina QIAO , Chengquan ZHANG , Kun YAO , Junyu HAN
CPC classification number: G06V30/19127 , G06V30/16
Abstract: A method for recognizing text includes: obtaining a first feature map of an image; for each target feature unit, performing a feature enhancement process on a plurality of feature values of the target feature unit respectively based on the plurality of feature values of the target feature unit, in which the target feature unit is a feature unit in the first feature map along a feature enhancement direction; and performing a text recognition process on the image based on the first feature map after the feature enhancement process.
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公开(公告)号：US20220415071A1
公开(公告)日：2022-12-29
申请号：US17899712
申请日：2022-08-31
Inventor： Chengquan ZHANG , Pengyuan LV , Shanshan LIU , Meina QIAO , Yangliu XU , Liang WU , Jingtuo LIU , Junyu HAN , Errui DING , Jingdong WANG
IPC: G06V30/19 , G06V30/18 , G06T9/00 , G06V30/262 , G06N20/00
Abstract: The present disclosure provides a training method of a text recognition model, a text recognition method, and an apparatus, relating to the technical field of artificial intelligence, and specifically, to the technical field of deep learning and computer vision, which can be applied in scenarios such as optional character recognition, etc. The specific implementation solution is: performing mask prediction on visual features of an acquired sample image, to obtain a predicted visual feature; performing mask prediction on semantic features of acquired sample text, to obtain a predicted semantic feature, where the sample image includes text; determining a first loss value of the text of the sample image according to the predicted visual feature; determining a second loss value of the sample text according to the predicted semantic feature; training, according to the first loss value and the second loss value, to obtain the text recognition model.
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