/LightField_NVS

Primary LanguagePython

SE(3) Equivariant Convolution and Transformer in Ray Space

PyTorch implementation of paper "SE(3) Equivariant Convolution and Transformer in Ray Space"

Environment

This work follows the architecture of the work: IBRNet: Learning Multi-View Image-Based Rendering and we use the same environment. To create an anaconda environment:

conda env create -f environment.yml
conda activate lightfield

Datasets

We use the same datasets as IBRNet, please follow the instruction to download the datasets.

Running

example of multiple GPUs:
python -m torch.distributed.launch --nproc_per_node=8 train.py --config configs/train.txt

example of a single GPU:
python train.py --config configs/train.txt