Web Development2025
AI Deepfake Detection System
DeepFake detector is an AI-based deepfake detection system designed to identify manipulated facial videos using deep learning. The system extracts representative video frames, preprocesses facial regions, and classifies videos as real or fake using a fine-tuned ConvNeXt-Tiny model. To improve transparency and trust, Grad-CAM visualizations highlight the regions that influenced the model's prediction, enabling users to understand why a video was classified as manipulated. The project focuses entirely on visual analysis without relying on audio or lip-sync features.

Real / Fake
Detection
Grad-CAM
Explainability
Video Frames
Input
Key highlights
- Visual-only deepfake detection
- ConvNeXt-Tiny transfer learning
- Frame extraction using OpenCV
- Video classification (Real/Fake)
- Grad-CAM explainability
- Automated preprocessing pipeline
- Face-focused visual analysis
- Model evaluation with standard metrics
- GPU-accelerated inference
- Research-oriented architecture
Technologies
PythonPyTorchConvNeXt-TinyOpenCVGrad-CAMNumPyPandasMatplotlib
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