Face age synthesis: A review on datasets, methods, and open research areas

A Kale, O Altun - Pattern Recognition, 2023 - Elsevier
Face age synthesis is the determination of how a person looks in the future or the past by
reconstructing their facial image. Determining the change in the human face over the years …

Deep face age progression: A survey

M Grimmer, R Ramachandra, C Busch - IEEE Access, 2021 - ieeexplore.ieee.org
Face Age Progression (FAP) refers to synthesizing face images while simulating ageing
effects, thus enabling predicting the future appearance of an individual. The generation of …

Multi-scale feature fusion model followed by residual network for generation of face aging and de-aging

DV Atkale, MM Pawar, SC Deshpande… - Signal, Image and Video …, 2022 - Springer
Face aging is one of the most interesting style transfer ideas due to the extraordinary
development in image synthesis succeeded by deep learning models that is the generative …

A Waste Copper Granules Rating System Based on Machine Vision

K Zhao, Y Cui, Z Liu, S Lian - arXiv preprint arXiv:2207.04575, 2022 - arxiv.org
In the field of waste copper granules recycling, engineers should be able to identify all
different sorts of impurities in waste copper granules and estimate their mass proportion …

PP-GAN: Style Transfer from Korean Portraits to ID Photos Using Landmark Extractor with GAN

J Si, S Kim - arXiv preprint arXiv:2306.13418, 2023 - arxiv.org
The objective of a style transfer is to maintain the content of an image while transferring the
style of another image. However, conventional research on style transfer has a significant …

Synthetic Face Aging Using CycleGAN

R Vyawahare, DHK Khanuja… - Available at SSRN …, 2022 - papers.ssrn.com
Abstract Generative Adversarial Neural Networks have become well liked framework in the
Computer Science and Artificial Intelligence fields. Human face and body changes with age …