STATE: Learning Structure and Texture Representations for Novel View Synthesis

This repository contains a pytorch implementation of STATE: Learning Structure and Texture Representations for Novel View Synthesis, CVMJ 2022.

Project Page
Supp.

Requirement

conda env create -f environment.yaml

Data

The datasets of Car and Chair can be downloaded from TBN.

Train

python train_car.py -c config_car.json [-r path_to_checkpoint]

Test

python test.py -c config_car.json -r path_to_checkpoint

Citation

@inproceedings{STATE,
  author = {Xinyi Jing and Qiao Feng and Yu-kun Lai and Jinsong Zhang and Yuanqiang Yu and Kun Li},
  title = {STATE: Learning structure and texture representations for novel view synthesis},
  booktitle = {Computational Visual Media},
  year={2022},
}