Blurred Images Lead to Bad Local Minima
Gal Katzhendler, Daphna Weinshall
TL;DR
This paper investigates how blurred images can cause optimization algorithms to become trapped in poor local minima, negatively impacting image processing tasks.
Contribution
It highlights the problem of blurred images leading to suboptimal local minima and discusses potential implications for image analysis methods.
Findings
Blurred images increase the likelihood of bad local minima
Optimization performance degrades with image blurring
Addressing blurring can improve model convergence
Abstract
Blurred Images Lead to Bad Local Minima
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Taxonomy
TopicsFace recognition and analysis · Advanced Vision and Imaging · Advanced Image Processing Techniques