5 citations · 12 across the 5 of their papers we have counts for
6 papers
Towards Learning Food Portion From Monocular Images With Cross-Domain Feature Adaptation
Zeman Shao, Shaobo Fang, Runyu Mao +5
We aim to estimate food portion size, a property that is strongly related to the presence of food object in 3D space, from single monocular images under real life setting. Specific…
Saliency-Aware Class-Agnostic Food Image Segmentation
Sri Kalyan Yarlagadda, Daniel Mas Montserrat, David Guerra +3
Advances in image-based dietary assessment methods have allowed nutrition professionals and researchers to improve the accuracy of dietary assessment, where images of food consumed…
An End-to-End Food Image Analysis System
Jiangpeng He, Runyu Mao, Zeman Shao +4
Modern deep learning techniques have enabled advances in image-based dietary assessment such as food recognition and food portion size estimation. Valuable information on the types…
Multi-Task Image-Based Dietary Assessment for Food Recognition and Portion Size Estimation
Jiangpeng He, Zeman Shao, Janine Wright +3
Deep learning based methods have achieved impressive results in many applications for image-based diet assessment such as food classification and food portion size estimation. Howe…
Learning eating environments through scene clustering
Sri Kalyan Yarlagadda, Sriram Baireddy, David Güera +3
It is well known that dietary habits have a significant influence on health. While many studies have been conducted to understand this relationship, little is known about the relat…
Single-View Food Portion Estimation: Learning Image-to-Energy Mappings Using Generative Adversarial Networks
Shaobo Fang, Zeman Shao, Runyu Mao +5
Due to the growing concern of chronic diseases and other health problems related to diet, there is a need to develop accurate methods to estimate an individual's food and energy in…