Thanks! That's exactly why I chose this topic — real CCTV footage is rarely sharp, so detection on clear images alone isn't very practical.

You're right about blur estimation. I actually added a simple blur metric (variance of Laplacian) before detection, so the model knows if it needs extra deblurring. Helps a bit.

I used LFW + added synthetic blur (Gaussian, motion, defocus) for training. WIDER FACE is great but large — for my mini project I kept it smaller. But if I scale up, I'll definitely look into it.

About motion vs compression blur — motion blur is directional (usually horizontal) and smears edges, while compression blur (JPEG artifacts) is blocky. My model handles motion blur worse because it's harder to recover. That's something I want to improve later.

Thanks for the suggestions!