arXiv:2212.06701 공식 코드 · Papers with Code

A Novel Approach For Generating Customizable Light Field Datasets for Machine Learning

Julia Huang, Toure Smith, Aloukika Patro, Vidhi Chhabra

제출 2022-12-13

원문 초록

To train deep learning models, which often outperform traditional approaches, large datasets of a specified medium, e.g., images, are used in numerous areas. However, for light field-specific machine learning tasks, there is a lack of such available datasets. Therefore, we create our own light field datasets, which have great potential for a variety of applications due to the abundance of information in light fields compared to singular images. Using the Unity and C# frameworks, we develop a novel approach for generating large, scalable, and reproducible light field datasets based on customizable hardware configurations to accelerate light field deep learning research.

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