avinashpaliwal/Super-SloMo
PyTorch implementation of Super SloMo, a deep neural network for estimating intermediate frames to produce smooth slow-motion videos.
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This repository implements the Super SloMo paper by Jiang et al., using a convolutional neural network to interpolate frames between existing video frames. The model learns to estimate optical flow and synthesize intermediate frames, enabling high-quality slow-motion video generation from standard frame-rate footage. It provides training code, pretrained models, and evaluation scripts with metrics like PSNR and SSIM.
Frequently asked
- What is avinashpaliwal/Super-SloMo?
- PyTorch implementation of Super SloMo, a deep neural network for estimating intermediate frames to produce smooth slow-motion videos.
- Is Super-SloMo open source?
- Yes — avinashpaliwal/Super-SloMo is open source, released under the MIT license.
- What language is Super-SloMo written in?
- avinashpaliwal/Super-SloMo is primarily written in Python.
- How popular is Super-SloMo?
- avinashpaliwal/Super-SloMo has 3k stars on GitHub.
- Where can I find Super-SloMo?
- avinashpaliwal/Super-SloMo is on GitHub at https://github.com/avinashpaliwal/Super-SloMo.