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ELEDNet (ECCV 2024)

Official repository for the ECCV 2024 paper, "Towards Real-world Event-guided Low-light Video Enhancement and Deblurring."

[Paper] [Supp]

Currently, this pages only includes information about the dataset and paper. I will soon be sharing more details on this pages.

Video Demos

Downloading the RELED datasets

Please download and unzip the RELED dataset.

• [RELED-Train] / [RELED-Test]

The dataset follows the below directory format:

├── RELED/
    ├── train/
    │   ├── 0000/
    │   │   ├── blur_processed/
    │   │   │   ├── 00000.png
    │   │   │   ├── ...
    │   │   │   └── 00148.png
    │   │   ├── gt_processed/
    │   │   │   ├── 00000.png
    │   │   │   ├── ...
    │   │   │   └── 00148.png
    │   │   ├── events/
    │   │   │   ├── 00000.npz
    │   │   │   ├── ...
    │   │   │   └── 00148.npz
    │   │   └── event_voxel/
    │   │       ├── 00000.npz
    │   │       ├── ...
    │   │       └── 00148.npz
    │   ├── 0001/
    │   │   ├── ...
    ├── test/
    │   ├── 0000/
    │   │   ├── ...
    │   ├── 0001/
    │   │   ├── ...

Sub-directory Descriptions:

• blur_processed: Contains low-light blurred images (*.png files).
• gt_processed: Contains normal-light sharp images (*.png files).
• events: Contains raw event data in .npz format.
• event_voxel: Contains event voxel data in .npz format.

Reading Raw Event Data (events) and Event Voxel Data(event_voxel):

To read event and event voxel data from .npz files using Python and NumPy:

import numpy as np

# Replace YOUR_EVENT_DIR with the path to the directory containing the .npz files for events
event_data = np.load('YOUR_EVENT_DIR/*.npz')['data']

Contact

If you have any question, please send an email to taewoo(intelpro@kaist.ac.kr)

License

The project codes and datasets can be used for research and education only.