AI Assisted Image Colorizer

DeOldify is an advanced deep learning-based AI project designed for automatic colorization and restoration of grayscale images and videos. It utilizes Generative Adversarial Networks (GANs) and Convolutional Neural Networks (CNNs) to generate high- quality, realistic colorizations with minimal user input. A key innovation in DeOldify is the NoGAN training approach, which combines pre-trained neural networks with adversarial learning to improve color accuracy and detail preservation. The model leverages a pre-trained ResNet as a feature extractor, enhancing image sharpness and reducing artifacts. Additionally, a self-attention mechanism refines the distribution of colors, ensuring natural and contextually appropriate results. These advancements make DeOldify highly effective for restoring historical photographs, enhancing old film footage, and improving medical imaging visualization. AI-assisted colorization has broad applications, including the revival of vintage photos, artistic reinterpretation of monochrome imagery, and aiding medical diagnostics by improving grayscale scan contrast. However, challenges such as color ambiguity, hallucination of incorrect colors, and dependence on training datasets remain areas for improvement

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Publication Details

Journal
International Journal of Advanced Research in Science Communication and Technology
Published
2025-03-08
DOI
https://doi.org/10.48175/ijarsct-23666
Primary Topic
Generative Adversarial Networks and Image Synthesis
Type
article
Field-Weighted Citation Impact
0.00
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article

AI Assisted Image Colorizer

N Kavyashree, T. N. Navya, P. L., N Bhanushree et al.
International Journal of Advanced Research in Science Communication and Technology
Generative Adversarial Networks and Image Synthesis
article

AI Assisted Image Colorizer

N Kavyashree, T. N. Navya, P. L., N Bhanushree, K Nanditha
article en

Abstract

DeOldify is an advanced deep learning-based AI project designed for automatic colorization and restoration of grayscale images and videos. It utilizes Generative Adversarial Networks (GANs) and Convolutional Neural Networks (CNNs) to generate high- quality, realistic colorizations with minimal user input. A key innovation in DeOldify is the NoGAN training approach, which combines pre-trained neural networks with adversarial learning to improve color accuracy and detail preservation. The model leverages a pre-trained ResNet as a feature extractor, enhancing image sharpness and reducing artifacts. Additionally, a self-attention mechanism refines the distribution of colors, ensuring natural and contextually appropriate results. These advancements make DeOldify highly effective for restoring historical photographs, enhancing old film footage, and improving medical imaging visualization. AI-assisted colorization has broad applications, including the revival of vintage photos, artistic reinterpretation of monochrome imagery, and aiding medical diagnostics by improving grayscale scan contrast. However, challenges such as color ambiguity, hallucination of incorrect colors, and dependence on training datasets remain areas for improvement

International Journal of Advanced Research in Science Communication and Technology
Shibaura Institute of Technology (JP)
Openalex Percentile: Top 97%
Generative Adversarial Networks and Image Synthesis
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AI Assisted Image Colorizer — N Kavyashree, T. N. Navya, et al. · International Journal of Advanced Research in Science Communication and Technology (2025) | TGRS Research Map | TGRS