@inproceedings{025a956443ab46e6b0e25eb1e2a4edda,
title = "A Deep Learning-based 6DoF Video Synthesizing Method Using Instant-NGPs",
abstract = "This paper introduces a new method for synthesizing six degree of freedom (6DoF) videos using neural radiance fields, which allows training from plain 2D images to render 3D scene at arbitrary viewports. Neural network model representing a previous timepoint is fine-Tuned to train models for subsequent timepoints. Additionally, instant neural graphics primitives (Instant-NGP) is applied for speed improvement. The proposed method achieved both improved objective quality for same number of training iterations and enhanced consistency between frames. Furthermore, it shows superiority over other methods for generating 6DoF videos, in terms of quality and time efficiency.",
keywords = "6DoF, Deep learning, Immersive video, Instant-NGP, MIV, NeRF, Virtual reality",
author = "Jaeyeol Choi and Jeong, \{Jong Beom\} and Junhyeong Park and Ryu, \{Eun Seok\}",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE International Conference on Visual Communications and Image Processing, VCIP 2023 ; Conference date: 04-12-2023 Through 07-12-2023",
year = "2023",
doi = "10.1109/VCIP59821.2023.10402618",
language = "English",
series = "2023 IEEE International Conference on Visual Communications and Image Processing, VCIP 2023",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2023 IEEE International Conference on Visual Communications and Image Processing, VCIP 2023",
}