JP2020098587A5 - - Google Patents

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JP2020098587A5
JP2020098587A5 JP2019212083A JP2019212083A JP2020098587A5 JP 2020098587 A5 JP2020098587 A5 JP 2020098587A5 JP 2019212083 A JP2019212083 A JP 2019212083A JP 2019212083 A JP2019212083 A JP 2019212083A JP 2020098587 A5 JP2020098587 A5 JP 2020098587A5
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shape
regression model
outline
image
module
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JP2019212083A
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Japanese (ja)
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JP7263216B2 (ja
JP2020098587A (ja
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JP2019212083A 2018-12-17 2019-11-25 ワッサースタイン距離を使用する物体形状回帰 Active JP7263216B2 (ja)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US16/222,062 US10943352B2 (en) 2018-12-17 2018-12-17 Object shape regression using wasserstein distance
US16/222,062 2018-12-17

Publications (3)

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JP2020098587A JP2020098587A (ja) 2020-06-25
JP2020098587A5 true JP2020098587A5 (https=) 2022-11-29
JP7263216B2 JP7263216B2 (ja) 2023-04-24

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US (1) US10943352B2 (https=)
EP (1) EP3671555A1 (https=)
JP (1) JP7263216B2 (https=)

Families Citing this family (13)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US12346432B2 (en) * 2018-12-31 2025-07-01 Intel Corporation Securing systems employing artificial intelligence
CN109993825B (zh) * 2019-03-11 2023-06-20 北京工业大学 一种基于深度学习的三维重建方法
DE102019210270A1 (de) * 2019-05-23 2020-11-26 Robert Bosch Gmbh Verfahren zum Trainieren eines Generative Adversarial Networks (GAN), Generative Adversarial Network, Computerprogramm, maschinenlesbares Speichermedium und Vorrichtung
US11068753B2 (en) * 2019-06-13 2021-07-20 Visa International Service Association Method, system, and computer program product for generating new items compatible with given items
CN113362351B (zh) * 2020-03-05 2025-02-28 阿里巴巴集团控股有限公司 一种图像处理方法、装置、电子设备以及存储介质
JP7704833B2 (ja) * 2020-07-17 2025-07-08 エーアイモーティブ ケーエフティー． オブジェクトセグメンテーションのための方法、データ処理システム、コンピュータプログラムプロダクト、およびコンピュータ可読媒体
US11823379B2 (en) * 2020-08-05 2023-11-21 Ping An Technology (Shenzhen) Co., Ltd. User-guided domain adaptation for rapid annotation from user interactions for pathological organ segmentation
US12387481B2 (en) * 2020-08-11 2025-08-12 Nvidia Corporation Enhanced object identification using one or more neural networks
US11762951B2 (en) * 2020-11-18 2023-09-19 Adobe Inc. Generative image congealing
CN112633350B (zh) * 2020-12-18 2021-10-01 湖北工业大学 一种基于图卷积的多尺度点云分类实现方法
US20220319635A1 (en) * 2021-04-05 2022-10-06 Nec Laboratories America, Inc. Generating minority-class examples for training data
US12488859B2 (en) * 2021-04-05 2025-12-02 Nec Corporation Peptide based vaccine generation system with dual projection generative adversarial networks
CN114627167B (zh) * 2022-02-25 2025-05-30 广州瑞多思医疗科技有限公司 基于神经网络的任意模态图像配准方法及设备

Family Cites Families (15)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US8358839B2 (en) * 2009-11-30 2013-01-22 Xerox Corporation Local regression methods and systems for image processing systems
CN103093490B (zh) * 2013-02-02 2015-08-26 浙江大学 基于单个视频摄像机的实时人脸动画方法
EP3136290A1 (en) * 2015-08-28 2017-03-01 Thomson Licensing Method and device for determining the shape of an object represented in an image, corresponding computer program product and computer readable medium
WO2018010101A1 (en) * 2016-07-12 2018-01-18 Microsoft Technology Licensing, Llc Method, apparatus and system for 3d face tracking
EP4131172A1 (en) * 2016-09-12 2023-02-08 Dassault Systèmes Deep convolutional neural network for 3d reconstruction of a real object
US10679046B1 (en) * 2016-11-29 2020-06-09 MAX-PLANCK-Gesellschaft zur Förderung der Wissenschaften e.V. Machine learning systems and methods of estimating body shape from images
US10902598B2 (en) * 2017-01-27 2021-01-26 Arterys Inc. Automated segmentation utilizing fully convolutional networks
US10497257B2 (en) * 2017-08-31 2019-12-03 Nec Corporation Parking lot surveillance with viewpoint invariant object recognition by synthesization and domain adaptation
US10614557B2 (en) * 2017-10-16 2020-04-07 Adobe Inc. Digital image completion using deep learning
US10733699B2 (en) * 2017-10-24 2020-08-04 Deep North, Inc. Face replacement and alignment
US10878529B2 (en) * 2017-12-22 2020-12-29 Canon Medical Systems Corporation Registration method and apparatus
US11445994B2 (en) * 2018-01-24 2022-09-20 Siemens Healthcare Gmbh Non-invasive electrophysiology mapping based on affordable electrocardiogram hardware and imaging
US20190347567A1 (en) * 2018-03-13 2019-11-14 Genetic Intelligence, Inc. Methods for data segmentation and identification
US11210836B2 (en) * 2018-04-03 2021-12-28 Sri International Applying artificial intelligence to generate motion information
US10614207B1 (en) * 2019-07-09 2020-04-07 Capital One Services, Llc Generating captcha images using variations of the same object

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