Institutional Repository of Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
Gourmet Photography Dataset for Aesthetic Assessment of Food Images | |
Kekai, Sheng1,2; Weiming, Dong1; Haibin, Huang3; Chongyang, Ma4; Bao-Gang, Hu1 | |
2018-12 | |
会议名称 | SIGGRAPH Asia 2018 Technical Briefs |
会议日期 | 2018-12-4 2018-12-7 |
会议地点 | Tokyo, Japan |
摘要 | In this study, we present the Gourmet Photography Dataset (GPD), which is the first large-scale dataset for aesthetic assessment of food photographs. We collect 12,000 food images together with human-annotated labels (i.e., aesthetically positive or negative) to build this dataset. We evaluate the performance of several popular machine learning algorithms for aesthetic assessment of food images to verify the effectiveness and importance of our GPD dataset. Experimental results show that deep convolutional neural networks trained on GPD can achieve comparable performance with human experts in this task, even on unseen food photographs. Our experiments also provide insights to support further study and applications related to visual analysis of food images. |
学科门类 | 工学 ; 工学::计算机科学与技术(可授工学、理学学位) |
收录类别 | EI |
语种 | 英语 |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/23890 |
专题 | 模式识别国家重点实验室_多媒体计算 模式识别国家重点实验室_模式分析与学习 |
作者单位 | 1.NLPR, Institute of Automation, Chinese Academy of Sciences 2.University of Chinese Academy of Sciences 3.Megvii/Face++ Research 4.Snap Inc. |
第一作者单位 | 模式识别国家重点实验室 |
推荐引用方式 GB/T 7714 | Kekai, Sheng,Weiming, Dong,Haibin, Huang,et al. Gourmet Photography Dataset for Aesthetic Assessment of Food Images[C],2018. |
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