TinyFace is a large scale face recognition benchmark to facilitate the investigation of natively LRFR (Low Resolution Face Recognition) at large scales (large gallery population sizes) in deep learning. The TinyFace dataset consists of 5,139 labelled facial identities given by 169,403 native LR face images (average 20×16 pixels) designed for 1:N recognition test. All the LR faces in TinyFace are collected from public web data across a large variety of imaging scenarios, captured under uncontrolled viewing conditions in pose, illumination, occlusion and background.