most citedHeteroscedastic Diffusion for Multi-Agent Trajectory Modeling

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

collaborators

7 papers

cs.CV2026

Deep Image Segmentation via Discriminant Feature Learning

Adam Dawid Sztamborski, Raül Pérez-Gonzalo, Antonio Agudo

Accurate image segmentation remains challenging, particularly in generating sharp, confident boundaries. While modern architectures have advanced the field, many of them still rely…

cs.LG20261 cited

Heteroscedastic Diffusion for Multi-Agent Trajectory Modeling

Guillem Capellera, Antonio Rubio, Luis Ferraz +1

Multi-agent trajectory modeling traditionally focuses on forecasting, often neglecting more general tasks like trajectory completion, which is essential for real-world applications…

cs.CV2026

End-to-End Image Compression with Segmentation Guided Dual Coding for Wind Turbines

Raül Pérez-Gonzalo, Andreas Espersen, Søren Forchhammer +1

Transferring large volumes of high-resolution images during wind turbine inspections introduces a bottleneck in assessing and detecting severe defects. Efficient coding must preser…

cs.CV2026

Unsupervised Modular Adaptive Region Growing and RegionMix Classification for Wind Turbine Segmentation

Raül Pérez-Gonzalo, Riccardo Magro, Andreas Espersen +1

Reliable operation of wind turbines requires frequent inspections, as even minor surface damages can degrade aerodynamic performance, reduce energy output, and accelerate blade wea…

cs.CV2026

Synthetic Craquelure Generation for Unsupervised Painting Restoration

Jana Cuch-Guillén, Antonio Agudo, Raül Pérez-Gonzalo

Cultural heritage preservation increasingly demands non-invasive digital methods for painting restoration, yet identifying and restoring fine craquelure patterns from complex brush…

cs.CV2026

Probabilistic Deep Discriminant Analysis for Wind Blade Segmentation

Raül Pérez-Gonzalo, Andreas Espersen, Antonio Agudo

Linear discriminant analysis improves class separability but struggles with non-linearly separable data. To overcome this, we introduce Deep Discriminant Analysis (DDA), which dire…