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Francisco Caetano

2 accepted papers

2026

Symmetrical Flow Matching: Unified Image Generation, Segmentation, and Classification with Score-Based Generative Models

AAAI 2026technical

Flow Matching has emerged as a powerful framework for learning continuous transformations between distributions, enabling high-fidelity generative modeling. This work introduces Symmetrical Flow Matching (SymmFlow), a new formulation that unifies semantic segmentation, classification, and image gene

Cited by 0SourcePDFScholar
2025

DisCoPatch: Taming Adversarially-driven Batch Statistics for Improved Out-of-Distribution Detection

ICCV 2025poster

Out-of-distribution (OOD) detection holds significant importance across many applications. While semantic and domain-shift OOD problems are well-studied, this work focuses on covariate shifts - subtle variations in the data distribution that can degrade machine learning performance. We hypothesize t…