KEYWORDS: 3D modeling, Visualization, 3D acquisition, Visual compression, 3D image processing, Video, Process modeling, Performance modeling, Visual process modeling, Quantization, Neural networks, Deep learning
This paper provides insight into the 3D scene compression represented by a neural implicit function. The goal of this paper is to introduce the aspects of implicit neural representation for 3D scenes such as NeRF (Neural Radiance Field) and propose a novel compression method for Neural Implicit representation for 3D scenes. We also provide the analysis of compression performance of 3D scene representation by using Neural implicit function.
KEYWORDS: Volume rendering, Video, Video compression, High efficiency video coding, Video coding, Voxels, Image fusion, Image compression, Discontinuities
The versatile video coding (VVC) [1] standard has doubled the number of intra prediction modes and MPM modes in the picture compared to the previous standard, High Efficiency Video Coding (HEVC) [2]. The most probable mode (MPM) is used to efficiently encode the intra prediction mode based on the neighboring intra-coded blocks. The VVC improves the compression performance by increasing the number of intra prediction mode and MPM candidates as the resolution of the video increases, but the texture map may be inefficient because the characteristics of the texture map are different from the general image. In this paper, we propose the efficient MPM candidate derivation on the Truncated Signed Distance Field (TSDF) [3] volume-based mesh property (texture map) for multi-view images. The proposed method shows 0.92% BD-rate performance gain for luma component in the random-access configuration [4].
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.