ETRI-Knowledge Sharing Plaform



논문 검색
구분 SCI
연도 ~ 키워드


학술대회 A Study on NeRF-based Synthetic Image Generation and Post-processing Method for Object Detection
Cited 0 time in scopus Download 5 time Share share facebook twitter linkedin kakaostory
문성원, 이지원, 이정수, 남도원, 유원영
International Conference on Information and Communication Technology Convergence (ICTC) 2022, pp.1560-1562
21HH5800, 영상 내 객체간 관계 분석 기반 해상 선박/구조물 상세 식별 콘텐츠 기술 개발, 남도원
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 제안 키워드
Computer Vision(CV), Neural network learning, Neural network training, Object detection, Post-processing method, machine Learning, synthetic image generation, training data