3D Convolutional Neural Networks for Accurate Reconstruction of Distorted Faces

Journal of Science Technology and Research (JSTAR) 5 (4):560-570 (2024)
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Abstract

The core objective of this project is to recognize and reconstruct distorted facial images, particularly in the context of accidents. This involves using deep learning techniques to analyze the features of a distorted face and regenerate it into a recognizable form. Deep learning models are wellsuited for this task due to their ability to learn complex patterns and representations from data the input data consists of distorted facial images, typically obtained from MRI scans of accident victims. These images may contain various types of distortions such as swelling, bruising, or other injuries that affect facial appearance.

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