Large Scale Visual Food Recognition

doi:10.1109/TPAMI.2023.3237871

	Large Scale Visual Food Recognition
	Min, Weiqing 1,2; Wang, Zhiling 1,2; Liu, Yuxin 1,2; Luo, Mengjiang 1,2; Kang, Liping 3; Wei, Xiaoming 3; Wei, Xiaolin 3; Jiang, Shuqiang 1,2
	2023-08-01
发表期刊	IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
ISSN	0162-8828
卷号	45 期号:8 页码:9932-9949
摘要	Food recognition plays an important role in food choice and intake, which is essential to the health and well-being of humans. It is thus of importance to the computer vision community, and can further support many food-oriented vision and multimodal tasks, e.g., food detection and segmentation, cross-modal recipe retrieval and generation. Unfortunately, we have witnessed remarkable advancements in generic visual recognition for released large-scale datasets, yet largely lags in the food domain. In this paper, we introduce Food2K, which is the largest food recognition dataset with 2,000 categories and over 1 million images. Compared with existing food recognition datasets, Food2K bypasses them in both categories and images by one order of magnitude, and thus establishes a new challenging benchmark to develop advanced models for food visual representation learning. Furthermore, we propose a deep progressive region enhancement network for food recognition, which mainly consists of two components, namely progressive local feature learning and region feature enhancement. The former adopts improved progressive training to learn diverse and complementary local features, while the latter utilizes self-attention to incorporate richer context with multiple scales into local features for further local feature enhancement. Extensive experiments on Food2K demonstrate the effectiveness of our proposed method. More importantly, we have verified better generalization ability of Food2K in various tasks, including food image recognition, food image retrieval, cross-modal recipe retrieval, food detection and segmentation. Food2K can be further explored to benefit more food-relevant tasks including emerging and more complex ones (e.g., nutritional understanding of food), and the trained models on Food2K can be expected as backbones to improve the performance of more food-relevant tasks. We also hope Food2K can serve as a large scale fine-grained visual recognition benchmark, and contributes to the development of large scale fine-grained visual analysis.
关键词	Image recognition Visualization Task analysis Benchmark testing Representation learning Training Semantics Food dataset food recognition large-scale datasets fine-grained recognition
DOI	10.1109/TPAMI.2023.3237871
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[61972378] ; National Natural Science Foundation of China[62125207] ; National Natural Science Foundation of China[U1936203] ; National Natural Science Foundation of China[U19B2040]
WOS研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS记录号	WOS:001022958600044
出版者	IEEE COMPUTER SOC
引用统计	被引频次：45[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/21336
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Jiang, Shuqiang
作者单位	1.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 3.Meituan Grp, Beijing 100102, Peoples R China
推荐引用方式 GB/T 7714	Min, Weiqing,Wang, Zhiling,Liu, Yuxin,et al. Large Scale Visual Food Recognition[J]. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE,2023,45(8):9932-9949.
APA	Min, Weiqing.,Wang, Zhiling.,Liu, Yuxin.,Luo, Mengjiang.,Kang, Liping.,...&Jiang, Shuqiang.(2023).Large Scale Visual Food Recognition.IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE,45(8),9932-9949.
MLA	Min, Weiqing,et al."Large Scale Visual Food Recognition".IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 45.8(2023):9932-9949.