Case Study
Audio-Video Deepfake Detection System
Multimodal AI system for identifying manipulated videos with spatial and temporal features.
Architecture
Video frames are preprocessed before passing through the detection pipeline.
Spatial and temporal features are fused for classification and confidence scoring.
A Flask API exposes the model for real-time inference and integration.
Screenshots
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Inference
Multimodal prediction flow and confidence scoring.
Challenges
- Combining temporal and spatial signals without creating a fragile pipeline.
- Keeping inference fast enough for practical analysis.
- Returning a score that is useful rather than just a label.
Benchmarks
92% classification accuracy
Real-time inference
Explainable scoring
Lessons Learned
- Strong preprocessing often matters as much as model choice in media problems.
- Explainability improves trust when the output is meant for decision support.
Tech Stack
PyTorchOpenCVFlaskVision TransformersCNNs
Key Results
92% classification accuracy
Real-time inference
Explainable scoring