---
license: apache-2.0
tags:
- infrared
- image
- pretraining
size_categories:
- 1M<n<10M
---

<h1 align="center"> UNIP: Rethinking Pre-trained Attention Patterns for Infrared Semantic Segmentation </h1>

<p align="center">
  <a href='https://arxiv.org/abs/2502.02257'>
  <img src='https://img.shields.io/badge/Arxiv-2502.02257-A42C25?style=flat&logo=arXiv&logoColor=A42C25'></a>
  <a href='https://huggingface.co/casiatao/UNIP'>
  <img src='https://img.shields.io/badge/%F0%9F%A4%97%20Model-UNIP-yellow'></a>
</p>

Code: https://github.com/casiatao/UNIP

## 📖 Introduction
This repository releases the InfMix dataset, a pre-training dataset consisting of 541,088 infrared images collected from 23 sub-datasets.

Scripts for unzipping
```
#!/bin/bash

LOGFILE="unzip_errors.log"
: > "$LOGFILE"  # Clear the log file

files=(*.zip *.z??)
declare -A processed

for file in "${files[@]}"; do
  [[ -f "$file" ]] || continue

  # Extract the base name without extension, e.g., a.zip -> a, a.z01 -> a
  base="${file%%.*}"

  # Skip if already processed
  if [[ -n "${processed[$base]}" ]]; then
    continue
  fi
  processed[$base]=1

  # If the target directory already exists, skip extraction
  if [[ -d "$base" ]]; then
    echo "Directory $base exists, skipping unzip of $base.zip"
    continue
  fi

  mkdir -p "$base"

  # Extract using 7z (quiet mode), redirect errors to log, and check success
  if ! 7za x -y "$base.zip" -o"$base" >>"$LOGFILE" 2>&1; then
    echo "[$(date '+%F %T')] Error: Failed to 7z extract $base.zip" >> "$LOGFILE"
    echo "Skipping $base.zip due to error."
    rm -rf "$base"
    continue
  fi
done

echo "Unzip task completed. Please check $LOGFILE for error logs."
```

## Citation
If you find this repository helpful, please consider giving a like ❤️ and citing:
```bibtex
@inproceedings{
  zhang2025unip,
  title={{UNIP}: Rethinking Pre-trained Attention Patterns for Infrared Semantic Segmentation},
  author={Tao Zhang and Jinyong Wen and Zhen Chen and Kun Ding and Shiming Xiang and Chunhong Pan},
  booktitle={The Thirteenth International Conference on Learning Representations},
  year={2025},
  url={https://openreview.net/forum?id=Xq7gwsnhPT}
}
```