Towards Robust Image Stitching: An Adaptive Resistance Learning against Compatible Attacks

This repo is the official implementation of, “Towards Robust Image Stitching: An Adaptive Resistance Learning against Compatible Attacks”, Zhiying Jiang, Xingyuan Li, Jinyuan Liu, Xin Fan, Risheng Liu*, Association for the Advancement of Artificial Intelligence (AAAI), 2024.

• [ArXiv]

Overview

Prerequisites

• Linux or macOS
• Python 3
• CPU or NVIDIA GPU + CUDA CuDNN

🔑 Installation

Type the command:

pip install -r requirements.txt

🤖 Download

Download the pre-trained model

• Google Drive
• Baidu Yun
  code: ​ 0817 ​

Download our collected dataset:

• Google Drive
• Baidu Yun
  code: ​ 0817 ​

Note

• For training, an NVIDIA GPU is strongly recommended for speed.
• You can train and test the model using the following commands, or choose the pre-trained checkpoint that we provide.
• For using custom data and pre-trained models, you need to replace the paths in the code with your own local paths.

ImageAlignment

• First, you need to train a image alignment model:

cd ImageAlignment
python train.py

• To test a trained alignment network:

python test.py

ImageReconstruction

• Second, you need to train a image reconstruction model:

cd ../ImageReconstruction
python train.py

• To test a trained reconstruction network:

python test.py

Then you can get the final robust stitching results.