Bhattacharjee,SushilMarcel,SébastienBrömme,ArslanBusch,ChristophDantcheva,AntitzaRathgeb,ChristianUhl,Andreas2017-09-262017-09-262017978-3-88579-664-0https://dl.gi.de/handle/20.500.12116/4645High-quality custom-made 3D masks are increasing becoming a serious threat to face recognition systems. This threat is driven, in part, by the falling cost of manufacturing such masks. Research in face presentation-attack detection (PAD) in general, and also specifically for 3D-mask based attacks, has mostly concentrated on imagery in the visible-light range of wavelengths (RGB). We look beyond imagery in the visible-light spectrum to find potentially easier solutions for the challenge of face presentation-attack detection (PAD). In particular, we explore the use of nearinfrared (NIR) and thermal imagery to detect print-, replay-, and 3D-mask-attacks. This preliminary study shows that both NIR and thermal imagery can potentially simplify the task of face-PAD.enFace Presentation Attack Detection3D-MasksRGB/depth camerasthermal camerasNIRLWIR1617-5468