5 citations · 9 across the 15 of their papers we have counts for
17 papers
ReSAGE-PAR: Representational Similarity Assessment for Generative Expansion in Pedestrian Attribute Recognition
Pablo Ayuso-Albizu, Pablo Carballeira, Juan C. SanMiguel +1
To address the limited diversity and data scarcity in Pedestrian Attribute Recognition (PAR), we explore image synthesis using diffusion models guided by attribute-based prompts. W…
MIRAGE: Retrieval and Generation of Multimodal Images and Texts for Medical Education
Miguel Diaz Benito, Cecilia Diana Albelda, Alvaro Garcia Martin +3
Access to diverse, well-annotated medical images with interactive learning tools is fundamental for training practitioners in medicine and related fields to improve their diagnosti…
Large Language Models Meet Extreme Multi-label Classification: Scaling and Multi-modal Framework
Diego Ortego, Marlon Rodríguez, Mario Almagro +3
Foundation models have revolutionized artificial intelligence across numerous domains, yet their transformative potential remains largely untapped in Extreme Multi-label Classifica…
Enhancing Zero-Shot Pedestrian Attribute Recognition with Synthetic Data Generation: A Comparative Study with Image-To-Image Diffusion Models
Pablo Ayuso-Albizu, Juan C. SanMiguel, Pablo Carballeira
Pedestrian Attribute Recognition (PAR) involves identifying various human attributes from images with applications in intelligent monitoring systems. The scarcity of large-scale an…
A Data-Centric Approach to Pedestrian Attribute Recognition: Synthetic Augmentation via Prompt-driven Diffusion Models
Alejandro Alonso, Sawaiz A. Chaudhry, Juan C. SanMiguel +3
Pedestrian Attribute Recognition (PAR) is a challenging task as models are required to generalize across numerous attributes in real-world data. Traditional approaches focus on com…
Unsupervised Class Generation to Expand Semantic Segmentation Datasets
Javier Montalvo, Álvaro García-Martín, Pablo Carballeira +1
Semantic segmentation is a computer vision task where classification is performed at a pixel level. Due to this, the process of labeling images for semantic segmentation is time-co…