18 citations · 73 across the 41 of their papers we have counts for
11 papers · 1 filter
An Improved Encoder-Decoder Framework for Food Energy Estimation
Jack Ma, Jiangpeng He, Fengqing Zhu
Dietary assessment is essential to maintaining a healthy lifestyle. Automatic image-based dietary assessment is a growing field of research due to the increasing prevalence of imag…
Personalized Food Image Classification: Benchmark Datasets and New Baseline
Xinyue Pan, Jiangpeng He, Fengqing Zhu
Food image classification is a fundamental step of image-based dietary assessment, enabling automated nutrient analysis from food images. Many current methods employ deep neural ne…
An Improved Upper Bound on the Rate-Distortion Function of Images
Zhihao Duan, Jack Ma, Jiangpeng He +1
Recent work has shown that Variational Autoencoders (VAEs) can be used to upper-bound the information rate-distortion (R-D) function of images, i.e., the fundamental limit of lossy…
Muti-Stage Hierarchical Food Classification
Xinyue Pan, Jiangpeng He, Fengqing Zhu
Food image classification serves as a fundamental and critical step in image-based dietary assessment, facilitating nutrient intake analysis from captured food images. However, exi…
Diffusion Model with Clustering-based Conditioning for Food Image Generation
Yue Han, Jiangpeng He, Mridul Gupta +2
Image-based dietary assessment serves as an efficient and accurate solution for recording and analyzing nutrition intake using eating occasion images as input. Deep learning-based…
An End-to-end Food Portion Estimation Framework Based on Shape Reconstruction from Monocular Image
Zeman Shao, Gautham Vinod, Jiangpeng He +1
Dietary assessment is a key contributor to monitoring health status. Existing self-report methods are tedious and time-consuming with substantial biases and errors. Image-based foo…
Long-Tailed Continual Learning For Visual Food Recognition
Jiangpeng He, Xiaoyan Zhang, Luotao Lin +3
Deep learning-based food recognition has made significant progress in predicting food types from eating occasion images. However, two key challenges hinder real-world deployment: (…
Single-Stage Heavy-Tailed Food Classification
Jiangpeng He, Fengqing Zhu
Deep learning based food image classification has enabled more accurate nutrition content analysis for image-based dietary assessment by predicting the types of food in eating occa…
Self-Supervised Visual Representation Learning on Food Images
Andrew Peng, Jiangpeng He, Fengqing Zhu
Food image analysis is the groundwork for image-based dietary assessment, which is the process of monitoring what kinds of food and how much energy is consumed using captured food…
Conditional Synthetic Food Image Generation
Wenjin Fu, Yue Han, Jiangpeng He +3
Generative Adversarial Networks (GAN) have been widely investigated for image synthesis based on their powerful representation learning ability. In this work, we explore the StyleG…
Online Class-Incremental Learning For Real-World Food Image Classification
Siddeshwar Raghavan, Jiangpeng He, Fengqing Zhu
Food image classification is essential for monitoring health and tracking dietary in image-based dietary assessment methods. However, conventional systems often rely on static data…