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IRVAL
IRVAL is a high-resolution infrared video dataset for infrared video processing and spatial-temporal video super-resolution research.
Dataset Summary
This repository currently contains 8 long infrared videos in .avi format.
According to the associated paper, IRVAL is a high-resolution infrared dataset comprising 108,512 video frames at a spatial resolution of 512×512. The data are collected using vanadium oxide (VOx) uncooled focal plane array detectors operating in the long-wave infrared (LWIR) band. The videos are captured from both vehicle-mounted and fixed surveillance platforms, covering real-world scenarios such as urban streets, vehicles, pedestrians, and roadside buildings.
Repository Structure
IRVAL/
├── README.md
├── LICENSE
└── videos/
├── irval_seq01.avi
├── irval_seq02.avi
├── irval_seq03.avi
├── irval_seq04.avi
├── irval_seq05.avi
├── irval_seq06.avi
├── irval_seq07.avi
└── irval_seq08.avi
Data Format
- Format:
.avi - Modality: thermal infrared video
- Resolution: 512×512
- Sensor type: VOx uncooled focal plane array detector
- Spectral band: long-wave infrared (LWIR)
Intended Use
This dataset is intended for research on:
- infrared video processing
- infrared video super-resolution
- spatial-temporal video super-resolution
- temporal consistency modeling
Notes
- This release contains 8 long infrared videos.
- This repository releases raw videos rather than pre-generated LR/HR pairs.
- Please make sure you comply with the dataset license and all applicable usage restrictions.
Citation
If you use this dataset, please cite:
@inproceedings{zhou2026thermal,
title={Thermal Diffusion Matters: Infrared Spatial-Temporal Video Super-Resolution through Heat Conduction Priors},
author={Mingxuan Zhou and Shuang Li and Yutang Zhang and Jing Geng and Yirui Shen and Jingxuan Kang and Fuzhen Zhuang and Shuigen Wang},
booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
year={2026}
}
Contact
For questions about the dataset, please contact: mingxuanzhou@bit.edu.cn
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