CN111095293A - 图像美学处理方法及电子设备 - Google Patents
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Abstract
本申请提供一种图像美学处理方法及电子设备,其中,图像美学评分模型生成方法包括:根据预设的卷积结构集合构建第一神经网络;获取图像分类神经网络,其中,所述图像分类神经网络用于对图像的场景进行分类;根据所述第一神经网络以及所述图像分类神经网络,得到第二神经网络,所述第二神经网络为包含场景信息的神经网络;根据所述第二神经网络,确定图像美学评分模型,所述图像美学评分模型的输出信息包括图像场景分类信息。该方法中,通过在主干神经网络上融合了场景信息,使得所得到的图像美学评分模型具有可解释性,同时,使用预设的卷积结构集合,可以提升图像美学评分模型的评分准确率。
Description
PCT国内申请,说明书已公开。
Claims (35)
- PCT国内申请,权利要求书已公开。
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PCT/CN2018/080533 WO2019114147A1 (zh) | 2017-12-15 | 2018-03-26 | 图像美学处理方法及电子设备 |
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Cited By (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN112418295A (zh) * | 2020-11-18 | 2021-02-26 | 北京三快在线科技有限公司 | 图像处理方法、装置、设备及存储介质 |
CN112650870A (zh) * | 2020-12-30 | 2021-04-13 | 北京天广汇通科技有限公司 | 一种训练图片排序模型的方法、图片排序的方法以及装置 |
CN112839167A (zh) * | 2020-12-30 | 2021-05-25 | Oppo(重庆)智能科技有限公司 | 图像处理方法、装置、电子设备及计算机可读介质 |
CN112967358A (zh) * | 2021-03-08 | 2021-06-15 | 上海微电机研究所(中国电子科技集团公司第二十一研究所) | 基于美学质量的数字相册筛选方法、装置和电子设备 |
CN113744012A (zh) * | 2020-08-10 | 2021-12-03 | 北京沃东天骏信息技术有限公司 | 一种信息处理方法、装置和存储介质 |
CN114283083A (zh) * | 2021-12-22 | 2022-04-05 | 杭州电子科技大学 | 一种基于解耦表示的场景生成模型的美学增强方法 |
CN114970654A (zh) * | 2021-05-21 | 2022-08-30 | 华为技术有限公司 | 数据处理方法、装置和终端 |
Families Citing this family (11)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US11367222B2 (en) * | 2018-04-20 | 2022-06-21 | Hewlett-Packard Development Company, L.P. | Three-dimensional shape classification and retrieval using convolutional neural networks and majority vote |
US11531840B2 (en) * | 2019-02-08 | 2022-12-20 | Vizit Labs, Inc. | Systems, methods, and storage media for training a model for image evaluation |
US10467504B1 (en) | 2019-02-08 | 2019-11-05 | Adhark, Inc. | Systems, methods, and storage media for evaluating digital images |
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US11494886B2 (en) * | 2020-05-29 | 2022-11-08 | Adobe Inc. | Hierarchical multiclass exposure defects classification in images |
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Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20160098844A1 (en) * | 2014-10-03 | 2016-04-07 | EyeEm Mobile GmbH | Systems, methods, and computer program products for searching and sorting images by aesthetic quality |
US20160179844A1 (en) * | 2014-12-17 | 2016-06-23 | Adobe Systems Incorporated | Neural Network Image Curation Control |
CN107018330A (zh) * | 2017-04-19 | 2017-08-04 | 中国电子科技集团公司电子科学研究院 | 一种实时拍照指导方法及装置 |
CN107146198A (zh) * | 2017-04-19 | 2017-09-08 | 中国电子科技集团公司电子科学研究院 | 一种照片智能裁剪方法及装置 |
US20170347259A1 (en) * | 2016-05-31 | 2017-11-30 | Samsung Electronics Co., Ltd. | Network use method using virtual sim and apparatus therefor |
Family Cites Families (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN104333707B (zh) * | 2014-11-25 | 2017-10-10 | 广东威创视讯科技股份有限公司 | 相机参数调整方法和系统 |
CN105528757B (zh) | 2015-12-08 | 2019-01-29 | 华南理工大学 | 一种基于内容的图像美学质量提升方法 |
CN105787510A (zh) * | 2016-02-26 | 2016-07-20 | 华东理工大学 | 基于深度学习实现地铁场景分类的系统及方法 |
CN107169586A (zh) * | 2017-03-29 | 2017-09-15 | 北京百度网讯科技有限公司 | 基于人工智能的资源组合优化方法、装置及存储介质 |
CN107153838A (zh) | 2017-04-19 | 2017-09-12 | 中国电子科技集团公司电子科学研究院 | 一种照片自动分级方法及装置 |
US10521705B2 (en) * | 2017-11-14 | 2019-12-31 | Adobe Inc. | Automatically selecting images using multicontext aware ratings |
-
2018
- 2018-03-26 WO PCT/CN2018/080533 patent/WO2019114147A1/zh active Application Filing
- 2018-03-26 US US16/771,063 patent/US11314988B2/en active Active
- 2018-03-26 CN CN201880060615.XA patent/CN111095293B/zh active Active
Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20160098844A1 (en) * | 2014-10-03 | 2016-04-07 | EyeEm Mobile GmbH | Systems, methods, and computer program products for searching and sorting images by aesthetic quality |
US20160179844A1 (en) * | 2014-12-17 | 2016-06-23 | Adobe Systems Incorporated | Neural Network Image Curation Control |
US20170347259A1 (en) * | 2016-05-31 | 2017-11-30 | Samsung Electronics Co., Ltd. | Network use method using virtual sim and apparatus therefor |
CN107018330A (zh) * | 2017-04-19 | 2017-08-04 | 中国电子科技集团公司电子科学研究院 | 一种实时拍照指导方法及装置 |
CN107146198A (zh) * | 2017-04-19 | 2017-09-08 | 中国电子科技集团公司电子科学研究院 | 一种照片智能裁剪方法及装置 |
Non-Patent Citations (1)
Title |
---|
谢燕娟等: "特征互补的图像美学质量评分方法" * |
Cited By (9)
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---|---|---|---|---|
CN113744012A (zh) * | 2020-08-10 | 2021-12-03 | 北京沃东天骏信息技术有限公司 | 一种信息处理方法、装置和存储介质 |
CN112418295A (zh) * | 2020-11-18 | 2021-02-26 | 北京三快在线科技有限公司 | 图像处理方法、装置、设备及存储介质 |
CN112650870A (zh) * | 2020-12-30 | 2021-04-13 | 北京天广汇通科技有限公司 | 一种训练图片排序模型的方法、图片排序的方法以及装置 |
CN112839167A (zh) * | 2020-12-30 | 2021-05-25 | Oppo(重庆)智能科技有限公司 | 图像处理方法、装置、电子设备及计算机可读介质 |
CN112839167B (zh) * | 2020-12-30 | 2023-06-30 | Oppo(重庆)智能科技有限公司 | 图像处理方法、装置、电子设备及计算机可读介质 |
CN112967358A (zh) * | 2021-03-08 | 2021-06-15 | 上海微电机研究所(中国电子科技集团公司第二十一研究所) | 基于美学质量的数字相册筛选方法、装置和电子设备 |
CN114970654A (zh) * | 2021-05-21 | 2022-08-30 | 华为技术有限公司 | 数据处理方法、装置和终端 |
CN114283083A (zh) * | 2021-12-22 | 2022-04-05 | 杭州电子科技大学 | 一种基于解耦表示的场景生成模型的美学增强方法 |
CN114283083B (zh) * | 2021-12-22 | 2024-05-10 | 杭州电子科技大学 | 一种基于解耦表示的场景生成模型的美学增强方法 |
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US11314988B2 (en) | 2022-04-26 |
US20210182613A1 (en) | 2021-06-17 |
CN111095293B (zh) | 2023-09-12 |
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