31 citations · 82 across the 7 of their papers we have counts for
7 papers
ICPR 2026 Competition on Low-Resolution License Plate Recognition
Rayson Laroca, Valfride Nascimento, Donggun Kim +19
Low-Resolution License Plate Recognition (LRLPR) remains a challenging problem in real-world surveillance scenarios, where long capture distances, compression artifacts, and advers…
Toward Unified Fine-Grained Vehicle Classification and Automatic License Plate Recognition
Gabriel E. Lima, Valfride Nascimento, Eduardo Santos +3
Extracting vehicle information from surveillance images is essential for intelligent transportation systems, enabling applications such as traffic monitoring and criminal investiga…
LPLC: A Dataset for License Plate Legibility Classification
Lucas Wojcik, Gabriel E. Lima, Valfride Nascimento +3
Automatic License Plate Recognition (ALPR) faces a major challenge when dealing with illegible license plates (LPs). While reconstruction methods such as super-resolution (SR) have…
Toward Advancing License Plate Super-Resolution in Real-World Scenarios: A Dataset and Benchmark
Valfride Nascimento, Gabriel E. Lima, Rafael O. Ribeiro +3
Recent advancements in super-resolution for License Plate Recognition (LPR) have sought to address challenges posed by low-resolution (LR) and degraded images in surveillance, traf…
Enhancing License Plate Super-Resolution: A Layout-Aware and Character-Driven Approach
Valfride Nascimento, Rayson Laroca, Rafael O. Ribeiro +2
Despite significant advancements in License Plate Recognition (LPR) through deep learning, most improvements rely on high-resolution images with clear characters. This scenario doe…
Super-Resolution of License Plate Images Using Attention Modules and Sub-Pixel Convolution Layers
Valfride Nascimento, Rayson Laroca, Jorge de A. Lambert +2
Recent years have seen significant developments in the field of License Plate Recognition (LPR) through the integration of deep learning techniques and the increasing availability…