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Patent Agency Ranking
公开(公告)号：US11775574B2
公开(公告)日：2023-10-03
申请号：US17182987
申请日：2021-02-23
Inventor： Yulin Li , Xiameng Qin , Ju Huang , Qunyi Xie , Junyu Han
IPC: G06F16/00 , G06F16/36 , G06F40/279 , G06F18/25 , G06V10/764 , G06V10/80 , G06V10/82 , G06V10/44 , G06V10/426 , G06N3/02
CPC classification number: G06F16/367 , G06F18/253 , G06F40/279 , G06V10/426 , G06V10/454 , G06V10/764 , G06V10/811 , G06V10/82 , G06N3/02
Abstract: A method for visual question answering, a computer device implementing the method and a medium for storing instructions on performing the method are provided. 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.
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公开(公告)号：US20230042234A1
公开(公告)日：2023-02-09
申请号：US17972253
申请日：2022-10-24
Inventor： Yangliu XU , Qunyi Xie , Yi Chen , Xiameng Qin , Chengquan Zhang , Kun Yao
IPC: G06N3/08
Abstract: A method for training a model includes: obtaining a scene image, second actual characters in the scene image and a second construct image; obtaining first features and first recognition characters of characters obtained by performing character recognition on the scene image using the model to be trained; obtaining second features of characters obtained by performing character recognition on the second construct image using the training auxiliary model; and obtaining a character recognition model by adjusting model parameters of the model to be trained based on the first recognition characters, the second actual characters, the first features and the second features.
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公开(公告)号：US20220148324A1
公开(公告)日：2022-05-12
申请号：US17581047
申请日：2022-01-21
Inventor： Xiameng QIN , Yulin Li , Ju Huang , Qunyi Xie , Chengquan Zhang , Kun Yao , Jingtuo Liu , Junyu Han
IPC: G06V30/18 , G06V30/24 , G06V30/148 , G06V30/19
Abstract: Provided are a method and apparatus for extracting information about a negotiable instrument, an electronic device and a storage medium. The method includes inputting a to-be-recognized negotiable instrument into a pretrained deep learning network and obtaining a visual image corresponding to the to-be-recognized negotiable instrument through the deep learning network;
matching the visual image corresponding to the to-be-recognized negotiable instrument with a visual image corresponding to each negotiable-instrument template in a preconstructed base template library; and in response to the visual image corresponding to the to-be-recognized negotiable instrument successfully matching a visual image corresponding to one negotiable-instrument template in the base template library, extracting structured information of the to-be-recognized negotiable instrument by using the negotiable-instrument template.-
公开(公告)号：US11768876B2
公开(公告)日：2023-09-26
申请号：US17161466
申请日：2021-01-28
Inventor： Xiameng Qin , Yulin Li , Qunyi Xie , Ju Huang , Junyu Han
IPC: G06F16/9032 , G06F16/583 , G06F16/532 , G06F40/279 , G06N3/04 , G06N3/088 , G06F18/213 , G06F18/25 , G06V10/25 , G06V10/764 , G06V10/80 , G06V10/82 , G06V10/44
CPC classification number: G06F16/90332 , G06F16/532 , G06F16/583 , G06F18/213 , G06F18/253 , G06F40/279 , G06N3/04 , G06N3/088 , G06V10/25 , G06V10/454 , G06V10/764 , G06V10/806 , G06V10/82 , G06V2201/07
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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公开(公告)号：US11756170B2
公开(公告)日：2023-09-12
申请号：US17151783
申请日：2021-01-19
Inventor： Qunyi Xie , Xiameng Qin , Yulin Li , Junyu Han , Shengxian Zhu
CPC classification number: G06T5/006 , G06N3/08 , G06T5/30 , G06T2207/20081 , G06T2207/20084 , G06T2207/30176
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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