20 citations · 50 across the 9 of their papers we have counts for
5 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…