SplatFlow: Learning Multi-frame Optical Flow via Splatting

This repository contains the source code for our paper:

• SplatFlow: Learning Multi-frame Optical Flow via Splatting (IJCV 2024) | Paper

Updates

• [April 24, 2024] 📣 The code of SplatFlow is now available!
• [January 02, 2024] 📣 The paper of SplatFlow is accepted by IJCV 2024!

Environment

• NVIDIA 3090 GPU
• CUDA 11.1
• Python 3.8
• PyTorch 1.8.2

Create a virtual environment and activate it.

conda create -n splatflow python=3.8
conda activate splatflow

Dependencies

pip install torch==1.8.2 --extra-index-url https://download.pytorch.org/whl/lts/1.8/cu111
pip install einops==0.4.1
pip install cupy-cuda111
pip install pillow==9.5.0
pip install opencv-python==4.1.2.30

Quick start

To make the model (with weights after K-finetune) infer on KITTI data, run

python main.py

Weights extraction code: sm11

Acknowledgments

We would like to thank RAFT, GMA and SoftSplat for publicly releasing their code and data.

Citing this Work

If you find our repository useful, please consider giving it a star ⭐ and citing our paper in your work:

@article{wang2024splatflow,
  title={SplatFlow: Learning Multi-frame Optical Flow via Splatting},
  author={Wang, Bo and Zhang, Yifan and Li, Jian and Yu, Yang and Sun, Zhenping and Liu, Li and Hu, Dewen},
  journal={International Journal of Computer Vision},
  pages={1--23},
  year={2024},
  publisher={Springer}
}