116 citations · 477 across the 58 of their papers we have counts for
75 papers
MUMINS: Metadata-conditioned Uncertainty-aware Medical Image Next-state Synthesis
Anna Oliveras, Roger Marí, Rafael Redondo +7
Forecasting anatomical changes such as tumor growth and neurodegeneration is a challenging generative vision task. Morphological evolution is subtle relative to static anatomy, hig…
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…
LAND: Lung and Nodule Diffusion for 3D Chest CT Synthesis with Anatomical Guidance
Anna Oliveras, Roger Marí, Rafael Redondo +6
This work introduces a new latent diffusion model to generate high-quality 3D chest CT scans conditioned on 3D anatomical masks. The method synthesizes volumetric images of size 25…
DADO: A Depth-Attention framework for Object Discovery
Federico Gonzalez, Estefania Talavera, Petia Radeva
Unsupervised object discovery, the task of identifying and localizing objects in images without human-annotated labels, remains a significant challenge and a growing focus in compu…
Stochastic-based Patch Filtering for Few-Shot Learning
Javier Rodenas, Eduardo Aguilar, Petia Radeva
Food images present unique challenges for few-shot learning models due to their visual complexity and variability. For instance, a pasta dish might appear with various garnishes on…