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Genebody-Benchmarks

This repository contains the training and evaluation code for NeuralBody, NeuralVolumes, NeuralHumanRendering, NeuralTexture, A-NeRF and IBRNet to perform novel-view synthesis on Genebody dataset. Following benchmark tables are also shown in the paper.

The code for each method is on the branches of this repository. To re-implement the results on GeneBody, please download the pretrained models in the Model Zoo first, and prepare the environment and dataset based on the README.md on each branch.

News

[29/04/22]: First version of benchmarks released, containing 5 case-specific methods and 1 generalizable methods.

Benchmarks

Case-specific Methods on Genebody

ModelPSNRSSIMLPIPSckpts
NV19.860.7740.267ckpts
NHR20.050.8000.155ckpts
NT21.680.8810.152ckpts
NB20.730.8780.231ckpts
A-Nerf15.570.5080.242ckpts

(see detail why A-Nerf's performance is counterproductive in issue)

Generalizable Methods on Genebody

ModelPSNRSSIMLPIPSckpts
PixelNeRF (Our implemetation coming soon)24.150.9030.122
IBRNet23.610.8360.177ckpts

Citation

@article{cheng2022generalizable,
    title={Generalizable Neural Performer: Learning Robust Radiance Fields for Human Novel View Synthesis},
    author={Cheng, Wei and Xu, Su and Piao, Jingtan and Qian, Chen and Wu, Wayne and Lin, Kwan-Yee and Li, Hongsheng},
    journal={arXiv preprint arXiv:2204.11798},
    year={2022}
}