5 citations · 5 across the 5 of their papers we have counts for
Showing cs.CVShow all
3 papers · 1 filter
cs.CV2024
Hiding Faces in Plain Sight: Defending DeepFakes by Disrupting Face Detection
Delong Zhu, Yuezun Li, Baoyuan Wu +3
Face-swapping DeepFakes have become an escalating societal concern, attracting increasing attention in recent years. To counter this, we investigate a new proactive defense framewo…
cs.CV2024
Texture, Shape, Order, and Relation Matter: A New Transformer Design for Sequential DeepFake Detection
Yunfei Li, Yuezun Li, Baoyuan Wu +3
Sequential DeepFake detection is an emerging task that predicts the manipulation sequence in order. Existing methods typically formulate it as an image-to-sequence problem, employi…
cs.CV2024★ 5 cited
FreqBlender: Enhancing DeepFake Detection by Blending Frequency Knowledge
Hanzhe Li, Jiaran Zhou, Yuezun Li +3
Generating synthetic fake faces, known as pseudo-fake faces, is an effective way to improve the generalization of DeepFake detection. Existing methods typically generate these face…