activity
20142026
most citedA Robust Real-Time Automatic License Plate Recognition Based on the YOLO Detector

607 citations · 2.9k across the 65 of their papers we have counts for

collaborators

68 papers

cs.CV2026

VeriCam: A Verification Baseline for the Classification of Unknown Data

Lucas Wojcik, Gabriel E. Lima, Sergio M. Silva +2

The advent of foundation models have enabled a new era in zero-shot classification. Yet, key challenges persist. Despite their impressive generalization power that leverages the im…

cs.CV2026

A Benchmark for Vehicle Attribute Classification in Cross-Domain Surveillance Scenarios

Sergio M. Silva, Otavio T. Remer, Gabriel E. Lima +3

Vehicle attribute analysis is a key component of Intelligent Transportation Systems (ITS), supporting applications such as vehicle identification, traffic monitoring, and forensic…

cs.CV2026

Identity-Conditioned Latent Consistency Distillation for Face Synthesis

Tiago Kienen Chaves, Bernardo Biesseck, David Menotti

Diffusion models have achieved strong results in high-fidelity image synthesis, but their iterative sampling process makes large-scale generation computationally expensive. This li…

cs.CV2026

UFPR-PEs: A Brazilian Face Recognition Benchmark with Self-Declared Race/Color Labels

Alexandre Diano, Bernardo Biesseck, Gabriel Polo +4

While face recognition systems are widely deployed, ensuring their demographic reliability and robustness under uncontrolled visual conditions remains a critical challenge. To brid…

cs.CV2026

Evaluating 2D and 3D-Aware Vision Foundation Models for Vehicle Attribute Recognition

Alexandre V. Delazeri, Gabriel E. Lima, Eduil Nascimento +2

Vehicle attribute recognition is an important task in intelligent transportation systems, particularly when Automatic License Plate Recognition (ALPR) is unavailable or unreliable.…

cs.CV2026

Robust Face Super-Resolution and Recognition Through Multi-Feature Aggregation in Diffusion Models

Marcelo dos Santos, Rayson Laroca, João Carlos Raposo Neves +1

Images acquired in surveillance environments often suffer from conditions such as low resolution, variations in pose, irregular illumination, and occlusions. Due to the low quality…