most citedPre-NeRF 360: Enriching Unbounded Appearances for Neural Radiance Fields

1 citations · 2 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2024

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…

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

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…

cs.CV20241 cited

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…

cs.CV20231 cited

Pre-NeRF 360: Enriching Unbounded Appearances for Neural Radiance Fields

Ahmad AlMughrabi, Umair Haroon, Ricardo Marques +1

Neural radiance fields (NeRF) appeared recently as a powerful tool to generate realistic views of objects and confined areas. Still, they face serious challenges with open scenes,…