Neural Point Cloud Rendering via Depth Peeling Multi-Projection and Temporary Refine

被引：0
|
作者：
Ye K. [1 ]
Pan Q. [1 ]
Ren Z. [1 ]
机构：
[1] State Key Laboratory of CAD&CG, Zhejiang University, Hangzhou
来源：
Jisuanji Fuzhu Sheji Yu Tuxingxue Xuebao/Journal of Computer-Aided Design and Computer Graphics | 2023年 / 35卷 / 05期
关键词：
depth peeling; hair point cloud; neural rendering; temporary stability;
D O I：
10.3724/SP.J.1089.2023.19419
中图分类号：
学科分类号：
摘要：
To tackle the problem that the existing point cloud-based neural rendering network cannot render high-quality hair with temporal stability, a depth peeling and temporal refine network is presented. Depth peeling method projects point clouds in different layers; fuses the results to adapt to the translucency of the hair; input the trained results into the temporal refine network. This module uses the reprojection of the point cloud between adjacent frames to obtain the dependency relationship between the current frame and the previous frames, and generates the final result of the current frame with temporal stability. The experiment uses high-quality hair datasets generated by ray tracing, and the final results show that compared with the existing methods, the proposed method can obtain better temporal stability and rendering results. © 2023 Institute of Computing Technology. All rights reserved.
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页码：666 / 684
页数：18
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