Research Paper#Computer Vision, Object Detection, Image Quality🔬 ResearchAnalyzed: Jan 3, 2026 19:34
Open-Vocabulary Object Detection Performance in Low-Quality Images
Published:Dec 28, 2025 06:18
•1 min read
•ArXiv
Analysis
This paper addresses a practical and important problem: evaluating the robustness of open-vocabulary object detection models to low-quality images. The study's significance lies in its focus on real-world image degradation, which is crucial for deploying these models in practical applications. The introduction of a new dataset simulating low-quality images is a valuable contribution, enabling more realistic and comprehensive evaluations. The findings highlight the varying performance of different models under different degradation levels, providing insights for future research and model development.
Key Takeaways
Reference
“OWLv2 models consistently performed better across different types of degradation.”