构建首个4K级低光照夜视基准数据集，助力夜间图像增强研究
LENVIZ: A High-Resolution Low-Exposure Night Vision Benchmark Dataset
- 采集23万+帧多曝光低光图像，覆盖2.4万真实场景
- 含专家精修的高质量真实图像作为标注基准
- 适合图像增强、夜视系统、自动驾驶等领域研究者使用
低光照图像增强在夜视、监控和自动驾驶等领域至关重要。由于低照度环境下成像固有局限，该任务仍具挑战性。为此，我们提出低曝光夜视（LENVIZ）数据集，一个涵盖超过23万帧的多曝光基准数据集，包含2.4万个真实室内外场景（含/不含人），采用3种不同相机传感器拍摄，覆盖广泛光照条件、噪声水平与场景复杂度，是当前公开可用的最大4K分辨率基准数据集。数据集提供高质量人工生成的真实图像作为标注，每个多曝光低光场景均由专业摄影师精心编辑，确保最优画质。此外，我们对当前主流低光图像增强技术在该数据集上的表现进行了全面分析，指出了潜在改进方向。
原文摘要 · Abstract (English)
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.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。