Deepfake Detection on UADFV (Feature Fusion)
Deepfake classifier combining CNN and handcrafted HAAR/Gabor features.
I developed a deepfake detection pipeline that fuses CNN face features with handcrafted HAAR and Gabor descriptors. For this website, the reported result is from Task 1 only: evaluating UADFV with a model trained on UADFV.
Key outcomes:
- Two-branch architecture: resized face input (
60x60) plus handcrafted feature vector (30features). - Improved Task 1 AUC from handcrafted-only baseline (
0.84) to fusion model (0.93). - Built a full preprocessing and evaluation pipeline for frame-level prediction.
Tech stack:
- Python
- TensorFlow/Keras
- OpenCV
- Dlib
- HAAR and Gabor filters
Links:
- Project report PDF
- Code repository link will be added after refactoring.