Code for Multiple Video Frame Interpolation via Enhanced Deformable Separable Convolution [arXiv] .
Baidu Cloud : bdfu
We are good in the environment:
python 3.7
CUDA 10.1
Pytorch 1.0.0
opencv-python 4.2.0
numpy 1.18.1
cupy 6.0.0
We provide two versions of our model. The EDSC_s model was trained to generate the midpoint (in time) of the two input frames. And you can either choose the l1 or the lf model for distortion and perceptual quality, respectively.
We are good to run
python run.py --model EDSC_s --model_state EDSC_s_l1.ckpt --out out.png
The EDSC_m model is able to generate a frame at an arbirary time position. For instance, to generate an intermediate frame at t=0.1, we are good to run
python run.py --model EDSC_m --model_state EDSC_m.ckpt --time 0.1 --out out.png
Please see the paper for more details.
@article{EDSC,
author={Cheng, Xianhang and Chen, Zhenzhong},
journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
title={Multiple Video Frame Interpolation via Enhanced Deformable Separable Convolution},
year={2021},
doi={10.1109/TPAMI.2021.3100714}
}
Part of the code was adapted from sepconv-slomo. A huge thanks to the authors!
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent