Thermal face imagery, which captures the naturally emitted heat from the
face, is limited in availability compared to face imagery in the visible
spectrum. To help address this scarcity of thermal face imagery for research
and algorithm development, we present the DEVCOM Army Research Laboratory
Visible-Thermal Face Dataset (ARL-VTF). With over 500,000 images from 395
subjects, the ARL-VTF dataset represents, to the best of our knowledge, the
largest collection of paired visible and thermal face images to date. The data
was captured using a modern long wave infrared (LWIR) camera mounted alongside
a stereo setup of three visible spectrum cameras. Variability in expressions,
pose, and eyewear has been systematically recorded. The dataset has been
curated with extensive annotations, metadata, and standardized protocols for
evaluation. Furthermore, this paper presents extensive benchmark results and
analysis on thermal face landmark detection and thermal-to-visible face
verification by evaluating state-of-the-art models on the ARL-VTF dataset.

通过使用 3 个可见光谱相机的立体设置，联合一个现代的长波红外热成像相机技术，本研究构建了包含 50 万张视觉和热成像图片的数据集 ARL-VTF，用于人脸识别算法的研究和开发，并对这个大数据集的热成像特征进行了分析和评估。