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公开(公告)号：US20210406592A1
公开(公告)日：2021-12-30
申请号：US17182987
申请日：2021-02-23
Inventor： Yulin LI , Xiameng QIN , Ju HUANG , Qunyi XIE , Junyu HAN
IPC: G06K9/62 , G06K9/46 , G06F40/279
Abstract: The present disclosure provides a method for visual question answering. The method includes: acquiring an input image and an input question; constructing a visual graph based on the input image, wherein the visual graph comprises a first node feature and a first edge feature; constructing a question graph based on the input question, wherein the question graph comprises a second node feature and a second edge feature; performing a multimodal fusion on the visual graph and the question graph to obtain an updated visual graph and an updated question graph; determining a question feature based on the input question; determining a fusion feature based on the updated visual graph, the updated question graph and the question feature; and generating a predicted answer for the input image and the input question. The present disclosure further provides an apparatus for visual question answering, a computer device and a medium.
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2.发明公开公开(公告)号：US20240021000A1
公开(公告)日：2024-01-18
申请号：US18113178
申请日：2023-02-23
Inventor： Xiameng QIN , Yulin LI , Xiaoqiang ZHANG , Ju HUANG , Qunyi XIE , Kun YAO
IPC: G06V30/19 , G06V30/148
CPC classification number: G06V30/1918 , G06V30/15 , G06V30/19127 , G06V30/19147
Abstract: There is provided an image-based information extraction model, method, and apparatus, a device, and a storage medium, which relates to the field of artificial intelligence (AI) technologies, specifically to fields of deep learning, image processing, computer vision technologies, and is applicable to optical character recognition (OCR) and other scenarios. A specific implementation solution involves: acquiring a to-be-extracted first image and a category of to-be-extracted information; and inputting the first image and the category into a pre-trained information extraction model to perform information extraction on the first image to obtain text information corresponding to the category.
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公开(公告)号：US20230048495A1
公开(公告)日：2023-02-16
申请号：US17974183
申请日：2022-10-26
Inventor： Qunyi XIE , Xiameng QIN , Mengyi EN , Dongdong ZHANG , Ju HUANG , Yangliu XU , Yi CHEN , Kun YAO
IPC: G06V30/413 , G06V10/764 , G06V10/24 , G06V10/75 , G06V30/414
Abstract: A method and a platform of generating a document, 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 a text recognition scenario and other scenarios. The method includes: performing a category recognition on a document picture to obtain a target category result; determining a target structured model matched with the target category result; and performing, by using the target structured model, a structure recognition on the document picture to obtain a structure recognition result, so as to generate an electronic document based on the structure recognition result, wherein the structure recognition result includes a field attribute recognition result and a field position recognition result.
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公开(公告)号：US20220392242A1
公开(公告)日：2022-12-08
申请号：US17819838
申请日：2022-08-15
Abstract: A method for training a text positioning model includes: obtaining a sample image, where the sample image contains a sample text to be positioned and a text marking box for the sample text; inputting the sample image into a text positioning model to be trained to position the sample text, and outputting a prediction text box for the sample image; obtaining a sample prior anchor box corresponding to the sample image; and adjusting model parameters of the text positioning model based on the sample prior anchor box, the text marking box and the prediction text box, and continuing training the adjusted text positioning model based on a next sample image until model training is completed, to generate a target text positioning model.
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Patent Agency Ranking
公开(公告)号：US20220101642A1
公开(公告)日：2022-03-31
申请号：US17545765
申请日：2021-12-08
Inventor： Qunyi XIE , Yangliu XU , Xiameng QIN , Chengquan ZHANG
Abstract: The disclosure discloses a method for character recognition, an electronic device, and a storage medium. The technical solution includes: obtaining a test sample image and a test sample character both corresponding to a test task; performing fine-tuning on a trained meta-learning model based on the test sample image and the test sample character to obtain a test task model; obtaining a test image corresponding to the test task; and generating a test character corresponding to the test image by inputting the test image into the test task model.
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公开(公告)号：US20210192696A1
公开(公告)日：2021-06-24
申请号：US17151783
申请日：2021-01-19
Inventor： Qunyi XIE , Xiameng QIN , Yulin LI , Junyu HAN , Shengxian ZHU
Abstract: Embodiments of the present disclosure provide a method and apparatus for correcting a distorted document image, where the method for correcting a distorted document image includes: obtaining a distorted document image; and inputting the distorted document image into a correction model, and obtaining a corrected image corresponding to the distorted document image; where the correction model is a model obtained by training with a set of image samples as inputs and a corrected image corresponding to each image sample in the set of image samples as an output, and the image samples are distorted. By inputting the distorted document image to be corrected into the correction model, the corrected image corresponding to the distorted document image can be obtained through the correction model, which realizes document image correction end-to-end, improves accuracy of the document image correction, and extends application scenarios of the document image correction.
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公开(公告)号：US20230134615A1
公开(公告)日：2023-05-04
申请号：US18146839
申请日：2022-12-27
Inventor： Qunyi XIE , Dongdong ZHANG , Xiameng QIN , Mengyi EN , Yangliu XU , Yi CHEN , Ju HUANG , Kun YAO
IPC: G06F9/48 , G06F40/205 , G06F9/50
Abstract: A method of processing a task, an electronic device, and a storage medium are provided, which relate to a field of artificial intelligence, in particular to fields of deep learning and computer vision, and may be applied to OCR optical character recognition and other scenarios. The method includes: parsing labeled data to be processed according to a task type identification, to obtain task labeled data, a tag information of the task labeled data is matched with the task type identification, and the task labeled data includes first task labeled data and second task labeled data; training a model using the first task labeled data, to obtain candidate models, the model is determined according to the task type identification; and determining a target model from the candidate models according to a performance evaluation result obtained by performing performance evaluation on the plurality of candidate models using the second task labeled data.
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公开(公告)号：US20220253631A1
公开(公告)日：2022-08-11
申请号：US17501221
申请日：2021-10-14
Inventor： Yulin LI , Ju HUANG , Qunyi XIE , Xiameng QIN , Chengquan ZHANG , Jingtuo LIU
Abstract: The present disclosure discloses an image processing method, an electronic device and a storage medium, and relates to the field of artificial intelligence technologies, and particularly to the fields of computer vision technologies, deep learning technologies, or the like. The image processing method includes: acquiring a multi-modal feature of each of at least one text region in an image, the multi-modal feature including features in plural dimensions; performing a global attention processing operation on the multi-modal feature of each text region to obtain a global attention feature of each text region; determining a category of each text region based on the global attention feature of each text region; and constructing structured information based on text content and the category of each text region.
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公开(公告)号：US20210406468A1
公开(公告)日：2021-12-30
申请号：US17161466
申请日：2021-01-28
Inventor： Xiameng QIN , Yulin LI , Qunyi XIE , Ju HUANG , Junyu HAN
IPC: G06F40/279 , G06N3/08 , G06N3/04 , G06F16/532 , G06F16/583 , G06K9/20 , G06K9/62 , G06K9/46
Abstract: The present disclosure provides a method for visual question answering, which relates to a field of computer vision and natural language processing. The method includes: acquiring an input image and an input question; constructing a Visual Graph based on the input image, wherein the Visual Graph comprises a Node Feature and an Edge Feature; updating the Node Feature by using the Node Feature and the Edge Feature to obtain an updated Visual Graph; determining a question feature based on the input question; fusing the updated Visual Graph and the question feature to obtain a fused feature; and generating a predicted answer for the input image and the input question based on the fused feature. The present disclosure further provides an apparatus for visual question answering, a computer device and a non-transitory computer-readable storage medium.
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