This repository is about the High Speed Event and RGB (HS-ERGB) dataset, used in the 2021 CVPR paper TimeLens: Event-based Video Frame Interpolation by Stepan Tulyakov*, Daniel Gehrig*, Stamatios Georgoulis, Julius Erbach, Mathias Gehrig, Yuanyou Li, and Davide Scaramuzza.
For more information, visit our project page.
A pdf of the paper is available here. If you use this dataset, please cite this publication as follows:
@Article{Tulyakov21CVPR,
author = {Stepan Tulyakov and Daniel Gehrig and Stamatios Georgoulis and Julius Erbach and Mathias Gehrig and Yuanyou Li and
Davide Scaramuzza},
title = {{TimeLens}: Event-based Video Frame Interpolation},
journal = "IEEE Conference on Computer Vision and Pattern Recognition",
year = 2021,
}
Download the dataset from our project page.
The dataset structure is as follows
.
├── close
│ └── test
│ ├── baloon_popping
│ │ ├── events_aligned
│ │ └── images_corrected
│ ├── candle
│ │ ├── events_aligned
│ │ └── images_corrected
│ ...
│
└── far
└── test
├── bridge_lake_01
│ ├── events_aligned
│ └── images_corrected
├── bridge_lake_03
│ ├── events_aligned
│ └── images_corrected
...
Each events_aligned
folder contains events files with template filename %06d.npz
, and images_corrected
contains image files with template filename %06d.png
. In events_aligned
each event file with index n
contains events between images with index n-1
and n
, i.e. event file 000001.npz
contains events between images 000000.png
and 000001.png
. Moreover, images_corrected
also contains timestamp.txt
where image timestamps are stored. Note that in some folders there are more image files than event files. However, the image stamps in timestamp.txt
should match with the event files and the additional images can be ignored.
For a quick test download the dataset to a folder using the link sent by email.
wget download_link.zip -O /tmp/dataset.zip
cd /tmp
unzip /tmp/dataset.zip
cd hsergb/
Then download this repo
git clone git@github.com:uzh-rpg/rpg_hs_ergb_dataset.git
And run the test
python rpg_hs_ergb_dataset/test_loader.py --dataset_root . \
--dataset_type close \
--sequence spinning_umbrella \
--sample_index 400
This should open a window visualizing aligned events with a single image.