Deep learning model for human-intuitive shoeprint reconstruction

Muhammad Hassan, Yan Wang, Di Wang, Wei Pang, Daixi Li, You Zhou, Dong Xu, Sami Ur Rahman, Amin ur Rahman, Ahmed Fateh Ameen, Peiwu Qin

Abstract: Highlights•An end-to-end deep learning model focuses on shoeprint reconstruction for forensics.•Reconstruction of existing patterns together with the generation of missing regions.•Missing regions reconstruction is specifically designed based on the loss function.•The proposed model performs well for noisy, blurry, and partial input images.•Model outperforms state-of-the-art generative models in terms of human evaluation.