Oct. 26, 2022, 1:15 a.m. | Hui Guo, Xin Wang, Siwei Lyu

cs.CV updates on arXiv.org arxiv.org

The COVID pandemic has led to the wide adoption of online video calls in
recent years. However, the increasing reliance on video calls provides
opportunities for new impersonation attacks by fraudsters using the advanced
real-time DeepFakes. Real-time DeepFakes pose new challenges to detection
methods, which have to run in real-time as a video call is ongoing. In this
paper, we describe a new active forensic method to detect real-time DeepFakes.
Specifically, we authenticate video calls by displaying a distinct pattern …

arxiv deepfakes detection real-time video video conferencing

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne

Senior Machine Learning Engineer (MLOps)

@ Promaton | Remote, Europe

Research Scientist (Computer Science)

@ Nanyang Technological University | NTU Main Campus, Singapore

Intern - Sales Data Management

@ Deliveroo | Dubai, UAE (Main Office)