This is the official repository of our IEEE TIP paper HyperE2VID: Improving Event-Based Video Reconstruction via Hypernetworks by Burak Ercan, Onur Eker, Canberk Sağlam, Aykut Erdem, and Erkut Erdem.
- Our HyperE2VID paper has been accepted by IEEE Transactions on Image Processing.
- For more details please see our paper.
- For qualitative results please see our project website.
- For more results and experimental analyses of HyperE2VID, please see the interactive result analysis tool of EVREAL.
- Model codes are published under the model folder in this repository.
- The pretrained model of HyperE2VID can be found here.
- For evaluation and analysis of HyperE2VID model, please use the codes in EVREAL repository.
- Instructions to generate training data can be found in the datagen folder.
- Training codes will be published soon.
If you use code in this repo in an academic context, please cite the following:
@article{ercan2024hypere2vid,
title={{HyperE2VID}: Improving Event-Based Video Reconstruction via Hypernetworks},
author={Ercan, Burak and Eker, Onur and Saglam, Canberk and Erdem, Aykut and Erdem, Erkut},
journal={IEEE Transactions on Image Processing},
year={2024},
volume={33},
pages={1826--1837},
doi={10.1109/TIP.2024.3372460},
publisher={IEEE}}
- This work was supported in part by KUIS AI Center Research Award, TUBITAK-1001 Program Award No. 121E454, and BAGEP 2021 Award of the Science Academy to A. Erdem.
- This code borrows from or is inspired by the following open-source repositories: