92 citations · 264 across the 39 of their papers we have counts for
42 papers
Flexible Variable-Rate Image Feature Compression for Edge-Cloud Systems
Md Adnan Faisal Hossain, Zhihao Duan, Yuning Huang +1
Feature compression is a promising direction for coding for machines. Existing methods have made substantial progress, but they require designing and training separate neural netwo…
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…
A Visual Quality Assessment Method for Raster Images in Scanned Document
Justin Yang, Peter Bauer, Todd Harris +4
Image quality assessment (IQA) is an active research area in the field of image processing. Most prior works focus on visual quality of natural images captured by cameras. In this…
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…
QARV: Quantization-Aware ResNet VAE for Lossy Image Compression
Zhihao Duan, Ming Lu, Jack Ma +3
This paper addresses the problem of lossy image compression, a fundamental problem in image processing and information theory that is involved in many real-world applications. We s…
Improving Food Detection For Images From a Wearable Egocentric Camera
Yue Han, Sri Kalyan Yarlagadda, Tonmoy Ghosh +3
Diet is an important aspect of our health. Good dietary habits can contribute to the prevention of many diseases and improve the overall quality of life. To better understand the r…
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…
Efficient Feature Compression for Edge-Cloud Systems
Zhihao Duan, Fengqing Zhu
Optimizing computation in an edge-cloud system is an important yet challenging problem. In this paper, we consider a three-way trade-off between bit rate, classification accuracy,…
Simulating Personal Food Consumption Patterns using a Modified Markov Chain
Xinyue Pan, Jiangpeng He, Andrew Peng +1
Food image classification serves as the foundation of image-based dietary assessment to predict food categories. Since there are many different food classes in real life, conventio…
Lossy Image Compression with Quantized Hierarchical VAEs
Zhihao Duan, Ming Lu, Zhan Ma +1
Recent research has shown a strong theoretical connection between variational autoencoders (VAEs) and the rate-distortion theory. Motivated by this, we consider the problem of loss…
3DG-STFM: 3D Geometric Guided Student-Teacher Feature Matching
Runyu Mao, Chen Bai, Yatong An +2
We tackle the essential task of finding dense visual correspondences between a pair of images. This is a challenging problem due to various factors such as poor texture, repetitive…
Splicing Detection and Localization In Satellite Imagery Using Conditional GANs
Emily R. Bartusiak, Sri Kalyan Yarlagadda, David Güera +4
The widespread availability of image editing tools and improvements in image processing techniques allow image manipulation to be very easy. Oftentimes, easy-to-use yet sophisticat…
Out-Of-Distribution Detection In Unsupervised Continual Learning
Jiangpeng He, Fengqing Zhu
Unsupervised continual learning aims to learn new tasks incrementally without requiring human annotations. However, most existing methods, especially those targeted on image classi…
Exemplar-free Online Continual Learning
Jiangpeng He, Fengqing Zhu
Targeted for real world scenarios, online continual learning aims to learn new tasks from sequentially available data under the condition that each data is observed only once by th…
Opening the Black Box of Learned Image Coders
Zhihao Duan, Ming Lu, Zhan Ma +1
End-to-end learned lossy image coders (LICs), as opposed to hand-crafted image codecs, have shown increasing superiority in terms of the rate-distortion performance. However, they…
Online Continual Learning Via Candidates Voting
Jiangpeng He, Fengqing Zhu
Continual learning in online scenario aims to learn a sequence of new tasks from data stream using each data only once for training, which is more realistic than in offline mode as…
Motion Artifact Reduction In Photoplethysmography For Reliable Signal Selection
Runyu Mao, Mackenzie Tweardy, Stephan W. Wegerich +3
Photoplethysmography (PPG) is a non-invasive and economical technique to extract vital signs of the human body. Although it has been widely used in consumer and research grade wris…
Improving Dietary Assessment Via Integrated Hierarchy Food Classification
Runyu Mao, Jiangpeng He, Luotao Lin +3
Image-based dietary assessment refers to the process of determining what someone eats and how much energy and nutrients are consumed from visual data. Food classification is the fi…
Online Continual Learning For Visual Food Classification
Jiangpeng He, Fengqing Zhu
Food image classification is challenging for real-world applications since existing methods require static datasets for training and are not capable of learning from sequentially a…
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…