IJB–S: IARPA Janus Surveillance Video Benchmark

摘要

We present IJB-S dataset, an open-source IARPA Janus Surveillance Video Benchmark and associated protocols. The dataset consists of images and surveillance video collected from 202 subjects at a Department of Defense (DoD) training facility. Surveillance video was captured across multiple vignettes representative of a variety of real-world surveillance use cases that are particularly of interest to law enforcement and national security communities. Each video was annotated by human subject matter experts in order to generate ground truth identity and bounding box face labels. In total, over 10 million annotations were collected for the dataset. We present benchmark results utilizing state of the art deep learning approaches such as FaceNet. Our results illustrate and characterize the difficulty of the dataset.