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20182026
most citedA Robust Real-Time Automatic License Plate Recognition Based on the YOLO Detector

607 citations · 1.6k across the 47 of their papers we have counts for

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Showing 2026 · cs.CVShow all

16 papers · 2 filters

cs.CV2026

Generalizable Brain Tumor Segmentation with Self-Training and Tumor-Aware Deformations

Henrique Zan Grande, Jeovane Honorio Alves, Rayson Laroca +1

This work presents an approach to the Generalizability Across Tumors (BraTS-GoAT) task of the BraTS 2026 Challenge, which focuses on robust segmentation of brain tumor sub-regions…

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

Benchmarking Spatial, Spectral, and Self-Supervised Cues for Face Forgery Detection under Realistic Degradation

Lucas Cunha, Lucas Sotomaior, Lucas Gasperin +3

Face forgery detectors often achieve strong results on controlled benchmarks, but their reliability under realistic image degradations remains limited. This paper presents a standa…

cs.CV2026

Audio-Text Cross-Attention with Psycholinguistic Support Features for Ambivalence/Hesitancy Recognition

Luiz F. B. F. Martins, Rodrigo W. Pisaia, Matheus M. Girardi +5

We present a frame-independent audio-text system for the 3rd Ambivalence/Hesitancy Video Recognition Challenge at the 11th Affective & Behavior Analysis in-the-Wild (ABAW) Workshop…

cs.CV2026

Confidence-Aware Ensemble and Long-Word Refinement for Artistic Text Recognition

Lucas A. Dias, Henrique A. Schulz, Rafaela de Miranda +3

Artistic Text Recognition (ATR) remains challenging because word images often combine decorative fonts, curved layouts, object-like characters, clutter, and severe distortions. Thi…

cs.CV2026

On the Role of MRI Sequences in Cross-Dataset Generalization for Brain Tumor Segmentation

Henrique Zan Grande, João G. Pitol, Lucas B. Schuck +3

Brain tumor segmentation in magnetic resonance imaging (MRI) is a critical task for diagnosis and treatment planning. Despite the success of deep learning architectures such as U-N…

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…

cs.CV2026

Computer Vision for MOBA Analytics: A Dataset and Baseline for Visibility Analysis in Dota 2

Ricardo da Rocha Carvalho, Eloísa Oliveira, Luiz Bernardo Martins Kummer +2

Introduction: Most Multiplayer Online Battle Arena (MOBA) analytics studies rely on structured data, which does not directly capture what each team could actually see during a matc…

cs.CV2026

Toward Parking Spot Occupancy Recognition: A Self-Supervised Approach

Luan Marko Kujavski, Rayson Laroca, Paulo Lisboa de Almeida

As urban areas expand, automatic monitoring of parking lots becomes essential for efficient and sustainable cities. This work proposes a self-supervised approach for parking spot o…

cs.CV2026

Revisiting Vehicle Color Recognition in Long-Tailed Surveillance Scenarios

Vinícius Orrú, Bruno H. Foggiatto, Gabriel E. Lima +2

Vehicle color recognition is an important cue for vehicle identification in surveillance systems, especially when license plates are illegible due to low resolution, occlusion, mot…

cs.CV2026

CEZSAR: A Contrastive Embedding Method for Zero-Shot Action Recognition

Valter Estevam, Rayson Laroca, Helio Pedrini +1

This paper proposes a novel Zero-Shot Action Recognition~(ZSAR) method based on contrastive learning. In ZSAR, we aim to classify examples from classes that were missing during tra…

cs.CV2026

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…

cs.CV2026

LPLCv2: An Expanded Dataset for Fine-Grained License Plate Legibility Classification

Lucas Wojcik, Eduardo A. F. Machoski, Eduil Nascimento +2

Modern Automatic License Plate Recognition (ALPR) systems achieve outstanding performance in controlled, well-defined scenarios. However, large-scale real-world usage remains chall…

cs.CV2026★ 3 cited

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…

cs.CV2026★ 7 cited

Advancing Multinational License Plate Recognition Through Synthetic and Real Data Fusion: A Comprehensive Evaluation

Rayson Laroca, Valter Estevam, Gladston J. P. Moreira +2

Automatic License Plate Recognition is a frequent research topic due to its wide-ranging practical applications. While recent studies use synthetic images to improve License Plate…