KITTI-360

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Method

Point-NeRF: Point-based Neural Radiance Fields [Point-NeRF]
https://github.com/Xharlie/pointnerf

Submitted on 17 Nov. 2023 05:29 by
Yiyi Liao (MPI)

Running time:		1 s
Environment:		1 core @ 2.5 Ghz (C/C++)

Method Description:

Point-NeRF uses neural 3D point clouds associated with neural features
to model a radiance field.

Parameters:

n/a

Latex Bibtex:

@inproceedings{xu2022point,
title={Point-nerf: Point-based neural radiance fields},
author={Xu, Qiangeng and Xu, Zexiang and Philip, Julien and Bi, Sai
and Shu, Zhixin and Sunkavalli, Kalyan and Neumann, Ulrich},
booktitle={Proceedings of the IEEE/CVF Conference on Computer
Vision and Pattern Recognition},
pages={5438--5448},
year={2022}
}

Detailed Results

This page provides detailed results for the method(s) selected. For the first 10 test images, we display the synthesized image and an error image. The error image visualizes the SSIM at every pixel. As the range of SSIM is within [-1,1] with 1 indicating the best performance and -1 indicating the worst, we visualize 1 - (1 + SSIM) / 2 such that bright region means large error and dark means low error.

Test Set Average

PSNR	SSIM	LPIPS
19.44	0.796	0.266

Error