most citedSelf-Supervised Face Presentation Attack Detection with Dynamic Grayscale Snippets

1 citations · 3 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV20231 cited

Semi-Supervised learning for Face Anti-Spoofing using Apex frame

Usman Muhammad, Mourad Oussalah, Jorma Laaksonen

Conventional feature extraction techniques in the face anti-spoofing domain either analyze the entire video sequence or focus on a specific segment to improve model performance. Ho…

cs.CV20231 cited

Saliency-based Video Summarization for Face Anti-spoofing

Usman Muhammad, Mourad Oussalah, Jorma Laaksonen

With the growing availability of databases for face presentation attack detection, researchers are increasingly focusing on video-based face anti-spoofing methods that involve hund…

cs.CV20232 cited

Deep Ensemble Learning with Frame Skipping for Face Anti-Spoofing

Usman Muhammad, Md Ziaul Hoque, Mourad Oussalah +1

Face presentation attacks (PA), also known as spoofing attacks, pose a substantial threat to biometric systems that rely on facial recognition systems, such as access control syste…

cs.CV2022

Face Anti-Spoofing from the Perspective of Data Sampling

Usman Muhammad, Mourad Oussalah

Without deploying face anti-spoofing countermeasures, face recognition systems can be spoofed by presenting a printed photo, a video, or a silicon mask of a genuine user. Thus, fac…

cs.CV20221 cited

Self-Supervised Face Presentation Attack Detection with Dynamic Grayscale Snippets

Usman Muhammad, Mourad Oussalah

Face presentation attack detection (PAD) plays an important role in defending face recognition systems against presentation attacks. The success of PAD largely relies on supervised…