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Found 6 papers, 2 papers with code
Detecting Deepfake by Creating Spatio-Temporal Regularity Disruption
Specifically, by carefully examining the spatial and temporal properties, we propose to disrupt a real video through a Pseudo-fake Generator and create a wide range of pseudo-fake videos for training.
Delving into Sequential Patches for Deepfake Detection
Recent advances in face forgery techniques produce nearly visually untraceable deepfake videos, which could be leveraged with malicious intentions.
CORE: Consistent Representation Learning for Face Forgery Detection
Specifically, we first capture the different representations with different augmentations, then regularize the cosine distance of the representations to enhance the consistency.
Shallow VAEs with RealNVP Prior Can Perform as Well as Deep Hierarchical VAEs
Using powerful posterior distributions is a popular technique in variational inference.
On the Necessity and Effectiveness of Learning the Prior of Variational Auto-Encoder
Using powerful posterior distributions is a popular approach to achieving better variational inference.
Unsupervised Anomaly Detection via Variational Auto-Encoder for Seasonal KPIs in Web Applications
To ensure undisrupted business, large Internet companies need to closely monitor various KPIs (e. g., Page Views, number of online users, and number of orders) of its Web applications, to accurately detect anomalies and trigger timely troubleshooting/mitigation.
