← Back to all news
arXiv Computer Vision October 21, 2026 By Raghavendra Ramachandra, Narayan Vetrekar, Neha Naik, Rajendra Gad

Decoupled Representation Learning for Face Presentation Attack Detection under Smart Glass Capture

Read the original on arXiv Computer Vision →

The Flow has not summarised this story yet — read it at arXiv Computer Vision.

  • benchmarks
  • safety

One email a morning, machine-written

One email a day, machine-written, one click to leave. We never share your address.

Related stories

arXiv AI
Jul 3

CPG-PAD: Concept-Informed Prompts Guided Presentation Attack Detection

arXiv:2607. 01303v1 Announce Type: cross Abstract: Presentation Attack Detection (PAD) serves as a crucial safeguard for face recognition systems against presentation attacks such as printed photos, replayed videos, and 3D masks.

By Haoyuan Zhang, Xiangyu Zhu, Li Gao, Ajian Liu, Siran Peng, Zhen Lei
llmsmultimodalbenchmarks
More like this →
arXiv Computer Vision
Aug 25

Tomatoes, Potatoes, and Onions: Questioning the Need for Faces in Face Presentation Attack Detection

arXiv:2608.21455v1 Announce Type: new Abstract: Face presentation attack detection (PAD) is traditionally formulated as a face-specific problem, although many of the visual artifacts introduced by pr...

By Guray Ozgur, Fadi Boutros, Naser Damer
benchmarkssafety
More like this →
arXiv Computer Vision
Aug 25

Primitive-Driven Compositional Forensic Visual Prompting for Open-World Face Anti-Spoofing

arXiv:2608.17351v2 Announce Type: replace Abstract: Open-world face anti-spoofing must address both covariate and semantic shifts: source and target domains differ in imaging conditions, while target...

By Fangling Jiang, Qi Li, Bing Liu, Weining Wang, Quilin Huang, Zhenan Sun, Ming-Hsuan Yang
llmsbenchmarks
More like this →
arXiv AI
Jul 31

FAS-R1: A Unified Multi-Task MLLM for Reasoning Face Anti-Spoofing

arXiv:2607. 26432v1 Announce Type: cross Abstract: Face anti-spoofing (FAS) is increasingly expected to provide not only bona fide/spoof decisions, but also attack semantics and image-grounded evidence for human inspection.

By Hongyang Wang, Yichen Shi, Hongrui Li, Yiru Huo, Jun Feng, Zitong Yu
fine-tuning
More like this →
arXiv Machine Learning
Jun 11

Adv-TGD: Adversarial Text-Guided Diffusion for Face Recognition Impersonation Attacks

arXiv:2606. 11615v1 Announce Type: cross Abstract: The widespread adoption of face recognition (FR) technologies raises serious privacy concerns, as facial data can be exploited without consent.

By Omid Ahmadieh, Nima Karimian
llmsragdiffusionroboticsfine-tuningmultimodalbenchmarkssafety
More like this →
arXiv Machine Learning
Aug 11

LoRA-based Adaptation Alone Is Not Enough: Understanding the Limits of Foundation Models for Face Presentation Attack Detection

arXiv:2608. 09633v1 Announce Type: cross Abstract: Face presentation attack detection (PAD) aims to reliably detect a wide range of presentation attacks.

By Peter Lorenz, Anjith George, Marcel S\'ebastien
llmsfine-tuningbenchmarks
More like this →
About Pricing API Newsletter Sources Privacy Terms Refunds Accessibility Provider info Contact RSS

The Flow links to publishers and never republishes their articles. Summaries are machine-generated.

v1.1.0 · 5f852ea