Search Results for author: Weiqing Min

Found 15 papers, 6 papers with code

Deep Learning for Logo Detection: A Survey

no code implementations10 Oct 2022 Sujuan Hou, Jiacheng Li, Weiqing Min, Qiang Hou, Yanna Zhao, Yuanjie Zheng, Shuqiang Jiang

When logos are increasingly created, logo detection has gradually become a research hotspot across many domains and tasks.

Discriminative Semantic Feature Pyramid Network with Guided Anchoring for Logo Detection

1 code implementation31 Aug 2021 Baisong Zhang, Weiqing Min, Jing Wang, Sujuan Hou, Qiang Hou, Yuanjie Zheng, Shuqiang Jiang

Unlike general object detection, logo detection is a challenging task, especially for small logo objects and large aspect ratio logo objects in the real-world scenario.

Management object-detection +1

FoodLogoDet-1500: A Dataset for Large-Scale Food Logo Detection via Multi-Scale Feature Decoupling Network

1 code implementation10 Aug 2021 Qiang Hou, Weiqing Min, Jing Wang, Sujuan Hou, Yuanjie Zheng, Shuqiang Jiang

For that, we propose a novel food logo detection method Multi-scale Feature Decoupling Network (MFDNet), which decouples classification and regression into two branches and focuses on the classification branch to solve the problem of distinguishing multiple food logo categories.

Food recommendation

A review on vision-based analysis for automatic dietary assessment

no code implementations6 Aug 2021 Wei Wang, Weiqing Min, TianHao Li, Xiaoxiao Dong, Haisheng Li, Shuqiang Jiang

We also provide the latest ideas for future development of VBDA, e. g., fine-grained food analysis and accurate volume estimation.

Food Recognition Nutrition

Applications of knowledge graphs for food science and industry

no code implementations13 Jul 2021 Weiqing Min, Chunlin Liu, Leyi Xu, Shuqiang Jiang

The deployment of various networks (e. g., Internet of Things [IoT] and mobile networks), databases (e. g., nutrition tables and food compositional databases), and social media (e. g., Instagram and Twitter) generates huge amounts of food data, which present researchers with an unprecedented opportunity to study various problems and applications in food science and industry via data-driven computational methods.

Data Visualization graph construction +4

Large Scale Visual Food Recognition

no code implementations30 Mar 2021 Weiqing Min, Zhiling Wang, Yuxin Liu, Mengjiang Luo, Liping Kang, Xiaoming Wei, Xiaolin Wei, Shuqiang Jiang

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.

Fine-Grained Visual Recognition Food Recognition +3

Dataset Bias in Few-shot Image Recognition

no code implementations18 Aug 2020 Shuqiang Jiang, Yaohui Zhu, Chenlong Liu, Xinhang Song, Xiang-Yang Li, Weiqing Min

Second, we investigate performance differences on different datasets from dataset structures and different few-shot learning methods.

Few-Shot Learning

ISIA Food-500: A Dataset for Large-Scale Food Recognition via Stacked Global-Local Attention Network

no code implementations13 Aug 2020 Weiqing Min, Linhu Liu, Zhiling Wang, Zhengdong Luo, Xiaoming Wei, Xiaolin Wei, Shuqiang Jiang

To encourage further progress in food recognition, we introduce the dataset ISIA Food- 500 with 500 categories from the list in the Wikipedia and 399, 726 images, a more comprehensive food dataset that surpasses existing popular benchmark datasets by category coverage and data volume.

Food Recognition Management

LogoDet-3K: A Large-Scale Image Dataset for Logo Detection

1 code implementation12 Aug 2020 Jing Wang, Weiqing Min, Sujuan Hou, Shengnan Ma, Yuanjie Zheng, Shuqiang Jiang

LogoDet-3K creates a more challenging benchmark for logo detection, for its higher comprehensive coverage and wider variety in both logo categories and annotated objects compared with existing datasets.

Management Object Detection +1

Logo-2K+: A Large-Scale Logo Dataset for Scalable Logo Classification

1 code implementation11 Nov 2019 Jing Wang, Weiqing Min, Sujuan Hou, Shengnan Ma, Yuanjie Zheng, Haishuai Wang, Shuqiang Jiang

Moreover, we propose a Discriminative Region Navigation and Augmentation Network (DRNA-Net), which is capable of discovering more informative logo regions and augmenting these image regions for logo classification.

Classification Data Augmentation +2

Food Recommendation: Framework, Existing Solutions and Challenges

no code implementations15 May 2019 Weiqing Min, Shuqiang Jiang, Ramesh Jain

A growing proportion of the global population is becoming overweight or obese, leading to various diseases (e. g., diabetes, ischemic heart disease and even cancer) due to unhealthy eating patterns, such as increased intake of food with high energy and high fat.

Food recommendation

A Survey on Food Computing

no code implementations22 Aug 2018 Weiqing Min, Shuqiang Jiang, Linhu Liu, Yong Rui, Ramesh Jain

This is the first comprehensive survey that targets the study of computing technology for the food area and also offers a collection of research studies and technologies to benefit researchers and practitioners working in different food-related fields.

Computers and Society Multimedia

Food recognition and recipe analysis: integrating visual content, context and external knowledge

no code implementations22 Jan 2018 Luis Herranz, Weiqing Min, Shuqiang Jiang

The central role of food in our individual and social life, combined with recent technological advances, has motivated a growing interest in applications that help to better monitor dietary habits as well as the exploration and retrieval of food-related information.

Food Recognition Food recommendation +1

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