activity
20192023
most citedWhen Segmentation is Not Enough: Rectifying Visual-Volume Discordance Through Multisensor Depth-Refined Semantic Segmentation for Food Intake Tracking in Long-Term Care

27 citations · 31 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2023★ 3 cited

Transferring Knowledge for Food Image Segmentation using Transformers and Convolutions

Grant Sinha, Krish Parmar, Hilda Azimi +4

Food image segmentation is an important task that has ubiquitous applications, such as estimating the nutritional value of a plate of food. Although machine learning models have be…

cs.CV2023

NutritionVerse-Thin: An Optimized Strategy for Enabling Improved Rendering of 3D Thin Food Models

Chi-en Amy Tai, Jason Li, Sriram Kumar +4

With the growth in capabilities of generative models, there has been growing interest in using photo-realistic renders of common 3D food items to improve downstream tasks such as f…

cs.CV2023★ 1 cited

NutritionVerse-3D: A 3D Food Model Dataset for Nutritional Intake Estimation

Chi-en Amy Tai, Matthew Keller, Mattie Kerrigan +4

77% of adults over 50 want to age in place today, presenting a major challenge to ensuring adequate nutritional intake. It has been reported that one in four older adults that are…

cs.CV2020

Quantization in Relative Gradient Angle Domain For Building Polygon Estimation

Yuhao Chen, Yifan Wu, Linlin Xu +1

Building footprint extraction in remote sensing data benefits many important applications, such as urban planning and population estimation. Recently, rapid development of Convolut…

cs.CV2019★ 27 cited

When Segmentation is Not Enough: Rectifying Visual-Volume Discordance Through Multisensor Depth-Refined Semantic Segmentation for Food Intake Tracking in Long-Term Care

Kaylen J Pfisterer, Robert Amelard, Audrey G Chung +4

Malnutrition is a multidomain problem affecting 54% of older adults in long-term care (LTC). Monitoring nutritional intake in LTC is laborious and subjective, limiting clinical inf…