Summarizer

Summarizer is a Video Summarization framework for research. Most of the literature now focuses on Deep Learning models experimenting on a set of reference datasets. This repository gathers the key assets to ease this research into a single Python framework.

The four main components are: * Centralized, preprocessed and documented datasets * PyTorch implementation and bugfixes of the prominent models * A robust set of evaluation metrics to evaluate them This framework is dedicated at helping to design the next generation of Deep Learning models for Video Summarization. ## Datasets SumMe | TVSum | LOL :--------------------------:|:-------------------------:|:------------------------:  ||

Datasets ground truth scores distribution per video

## Acknowledgement The architecture of Summarizer was inspired by [K. Zhou et al.](https://github.com/KaiyangZhou/pytorch-vsumm-reinforce) and [J. Fajtl et al.](https://github.com/ok1zjf/VASNet). The preprocessed datasets were inspired by [K. Zhang et al.](https://github.com/kezhang-cs/Video-Summarization-with-LSTM). We thank them all for their leading contributions.