LENVIZ: A High-Resolution Low-Exposure Night Vision Benchmark Dataset

Manjushree Aithal; Rosaura G. VidalMata; Manikandtan Kartha; Gong Chen; Eashan Adhikarla; Lucas N. Kirsten; Zhicheng Fu; Nikhil A. Madhusudhana; Joe Nasti

arXiv · 2503.19804

LENVIZ: A High-Resolution Low-Exposure Night Vision Benchmark Dataset

Manjushree Aithal·Rosaura G. VidalMata·Manikandtan Kartha·Gong Chen·Eashan Adhikarla·Lucas N. Kirsten·Zhicheng Fu·Nikhil A. Madhusudhana·Joe Nasti

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Abstract

Low-light image enhancement is crucial for a myriad of applications, from night vision and surveillance, to autonomous driving. However, due to the inherent limitations that come in hand with capturing images in low-illumination environments, the task of enhancing such scenes still presents a formidable challenge. To advance research in this field, we introduce our Low Exposure Night Vision (LENVIZ) Dataset, a comprehensive multi-exposure benchmark dataset for low-light image enhancement comprising of over 230K frames showcasing 24K real-world indoor and outdoor, with-and without human, scenes. Captured using 3 different camera sensors, LENVIZ offers a wide range of lighting conditions, noise levels, and scene complexities, making it the largest publicly available up-to 4K resolution benchmark in the field. LENVIZ includes high quality human-generated ground truth, for which each multi-exposure low-light scene has been meticulously curated and edited by expert photographers to ensure optimal image quality. Furthermore, we also conduct a comprehensive analysis of current state-of-the-art low-light image enhancement techniques on our dataset and highlight potential areas of improvement.

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Manjushree Aithal, Rosaura G. VidalMata, Manikandtan Kartha, Gong Chen, Eashan Adhikarla, Lucas N. Kirsten, Zhicheng Fu, Nikhil A. Madhusudhana, Joe Nasti. 2025-03-25. LENVIZ: A High-Resolution Low-Exposure Night Vision Benchmark Dataset. https://arxiv.org/abs/2503.19804

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