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Conference Paper A Study on NeRF-based Synthetic Image Generation and Post-processing Method for Object Detection
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Authors
SungWon Moon, Jiwon Lee, Jungsoo Lee, Dowon Nam, Wonyoung Yoo
Issue Date
2022-10
Citation
International Conference on Information and Communication Technology Convergence (ICTC) 2022, pp.1560-1562
Publisher
IEEE
Language
English
Type
Conference Paper
DOI
https://dx.doi.org/10.1109/ICTC55196.2022.9952798
Abstract
Recently, the importance of securing data in the field of computer vision using machine learning is increasing. In this situation, research to use synthetic images as training data in fields where real images cannot be used for various reasons is ongoing. In particular, in the defense field, where it is difficult to know the characteristics of imaging devices, neural network learning using synthetic images is essential for the introduction of civilian technology. In this paper, we propose a method to use for object detection neural network training by generating synthetic images instead of real images and removing artifacts from the generated images.
KSP Keywords
Computer Vision(CV), Neural network learning, Neural network training, Object detection, Post-processing method, machine Learning, synthetic image generation, training data