1 citations · 2 across the 10 of their papers we have counts for
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MVSBoost: An Efficient Point Cloud-based 3D Reconstruction
Umair Haroon, Ahmad AlMughrabi, Ricardo Marques +1
Efficient and accurate 3D reconstruction is crucial for various applications, including augmented and virtual reality, medical imaging, and cinematic special effects. While traditi…
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…
MomentsNeRF: Leveraging Orthogonal Moments for Few-Shot Neural Rendering
Ahmad AlMughrabi, Ricardo Marques, Petia Radeva
We propose MomentsNeRF, a novel framework for one- and few-shot neural rendering that predicts a neural representation of a 3D scene using Orthogonal Moments. Our architecture offe…
FoodMem: Near Real-time and Precise Food Video Segmentation
Ahmad AlMughrabi, Adrián Galán, Ricardo Marques +1
Food segmentation, including in videos, is vital for addressing real-world health, agriculture, and food biotechnology issues. Current limitations lead to inaccurate nutritional an…
VolETA: One- and Few-shot Food Volume Estimation
Ahmad AlMughrabi, Umair Haroon, Ricardo Marques +1
Accurate food volume estimation is essential for dietary assessment, nutritional tracking, and portion control applications. We present VolETA, a sophisticated methodology for esti…