6 papers
When does fusing hand-crafted knowledge with learned representations pay? A cost-normalized benchmark of stacking, substitution, and interference
Ahmad AlMughrabi, Albert Clop, Benjamin Busam +2
Fusing prior knowledge with data-driven learning is attractive where data is scarce, yet no controlled account says when it helps, is redundant, or harms. We benchmark one fixed ha…
PerBite: A Curated Diagnostic Workflow for Bite-Aware Food Volume Estimation
Ahmad AlMughrabi, Farid Al-Areqi, David Fernández Gómez +4
Can a visually plausible food mesh be trusted to estimate the volume of consumed food? \method investigates this question using selected paired before- and after-consumption states…
BenchSeg: A Large-Scale Dataset and Benchmark for Multi-View Food Video Segmentation
Ahmad AlMughrabi, Guillermo Rivo, Carlos Jiménez-Farfán +6
Food image segmentation is a critical task for dietary analysis, enabling accurate estimation of food volume and nutrients. However, current methods suffer from limited multi-view…
VolTex: Food Volume Estimation using Text-Guided Segmentation and Neural Surface Reconstruction
Ahmad AlMughrabi, Umair Haroon, Ricardo Marques +1
Accurate food volume estimation is crucial for dietary monitoring, medical nutrition management, and food intake analysis. Existing 3D Food Volume estimation methods accurately com…
VolE: A Point-cloud Framework for Food 3D Reconstruction and Volume Estimation
Umair Haroon, Ahmad AlMughrabi, Thanasis Zoumpekas +2
Accurate food volume estimation is crucial for medical nutrition management and health monitoring applications, but current food volume estimation methods are often limited by mono…
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…