Band-Attention Modulation Network for Robust Face Forgery Detection

arXiv:2404.06022 · cs.CV, cs.AI, cs.MM · Submitted 2024-04-09 · Read on arXiv

cs.CV, cs.AI, cs.MM

Submitted: 2024-04-09

Updated: 2026-09-24

Code: https://github.com/deepfakes/faceswap

Terminology

• AUC — 21× in this paper · explained in 2 episodes
• Transformer — 15× in this paper · explained in 2 episodes
• Generalization — 8× in this paper · explained in 13 episodes
• Band Attention Modulation — 7× in this paper
• Ablation — 5× in this paper · explained in 1 episode
• Attention Mechanism — 5× in this paper · explained in 3 episodes
• Ablation Studies — 4× in this paper · explained in 1 episode
• Robustness — 4× in this paper · explained in 5 episodes
• Global Average-Pooling — 3× in this paper
• Image-based Video-Level — 3× in this paper
• Alignment — 2× in this paper · explained in 1 episode
• Transformer Architecture — 2× in this paper · explained in 2 episodes
• Ablation study — 1× in this paper · explained in 1 episode
• Accuracy — 1× in this paper · explained in 1 episode
• Adam — 1× in this paper · explained in 2 episodes
• Adaptability — 1× in this paper · explained in 1 episode
• Adaptation — 1× in this paper · explained in 1 episode
• Area Under the Receiver Operating Characteristic Curve — 1× in this paper
• Benchmark — 1× in this paper · explained in 2 episodes
• Catastrophic Forgetting — 1× in this paper · explained in 5 episodes
• Contrastive Learning — 1× in this paper · explained in 5 episodes
• Convolutional Neural Networks (CNNs) — 1× in this paper · explained in 2 episodes
• Core — 1× in this paper · explained in 2 episodes
• Data Augmentation — 1× in this paper · explained in 7 episodes
• Discrete Cosine Transformation — 1× in this paper
• Domain Adaptation — 1× in this paper · explained in 5 episodes
• Feature Extraction — 1× in this paper · explained in 2 episodes
• Frequency Coefficient Attention Modulation — 1× in this paper
• Global Max-Pooling — 1× in this paper
• Meta-learning — 1× in this paper · explained in 2 episodes
• Semantic Similarity — 1× in this paper · explained in 2 episodes
• Verification — 1× in this paper · explained in 2 episodes

Sources

• ForensicTransfer: Weakly-supervised Domain Adaptation for Forgery Detection
• The DeepFake Detection Challenge (DFDC) Dataset
• An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
• Detecting GAN-generated Imagery using Color Cues
• Discrepancy-Guided Reconstruction Learning for Image Forgery Detection
• Retentive Network: A Successor to Transformer for Large Language Models
• FakeSpotter: A Simple yet Robust Baseline for Spotting AI-Synthesized Fake Faces

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