1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.CV2022★ 1 cited
OrthoMAD: Morphing Attack Detection Through Orthogonal Identity Disentanglement
Pedro C. Neto, Tiago Gonçalves, Marco Huber +3
Morphing attacks are one of the many threats that are constantly affecting deep face recognition systems. It consists of selecting two faces from different individuals and fusing t…
cs.CV2022
SYN-MAD 2022: Competition on Face Morphing Attack Detection Based on Privacy-aware Synthetic Training Data
Marco Huber, Fadi Boutros, Anh Thi Luu +16
This paper presents a summary of the Competition on Face Morphing Attack Detection Based on Privacy-aware Synthetic Training Data (SYN-MAD) held at the 2022 International Joint Con…