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cs.CV2025

SAMJAM: Zero-Shot Video Scene Graph Generation for Egocentric Kitchen Videos

Joshua Li, Fernando Jose Pena Cantu, Emily Yu +3

Video Scene Graph Generation (VidSGG) is an important topic in understanding dynamic kitchen environments. Current models for VidSGG require extensive training to produce scene gra…

cs.CV2024

MetaFood3D: 3D Food Dataset with Nutrition Values

Yuhao Chen, Jiangpeng He, Gautham Vinod +11

Food computing is both important and challenging in computer vision (CV). It significantly contributes to the development of CV algorithms due to its frequent presence in datasets…

cs.CV2024

NutritionVerse: Empirical Study of Various Dietary Intake Estimation Approaches

Chi-en Amy Tai, Matthew Keller, Saeejith Nair +8

Accurate dietary intake estimation is critical for informing policies and programs to support healthy eating, as malnutrition has been directly linked to decreased quality of life.…

cs.CV2024

MetaFood CVPR 2024 Challenge on Physically Informed 3D Food Reconstruction: Methods and Results

Jiangpeng He, Yuhao Chen, Gautham Vinod +16

The increasing interest in computer vision applications for nutrition and dietary monitoring has led to the development of advanced 3D reconstruction techniques for food items. How…

cs.CV2024

Understanding the Limitations of Diffusion Concept Algebra Through Food

E. Zhixuan Zeng, Yuhao Chen, Alexander Wong

Image generation techniques, particularly latent diffusion models, have exploded in popularity in recent years. Many techniques have been developed to manipulate and clarify the se…

cs.CV2024

NutritionVerse-Direct: Exploring Deep Neural Networks for Multitask Nutrition Prediction from Food Images

Matthew Keller, Chi-en Amy Tai, Yuhao Chen +2

Many aging individuals encounter challenges in effectively tracking their dietary intake, exacerbating their susceptibility to nutrition-related health complications. Self-reportin…