lok-18/A2RNet
AAAI 2025 | A2RNet: Adversarial Attack Resilient Network for Robust Infrared and Visible Image Fusion
This tool helps improve the clarity and robustness of images by combining information from infrared and visible light cameras. It takes separate infrared and visible images, along with optional pseudo-labels for guidance, and produces a single fused image that is more resilient to 'adversarial attacks'—subtle alterations that can trick AI systems. This is ideal for professionals in fields like surveillance, autonomous driving, or medical imaging who rely on AI for detection and segmentation tasks.
No commits in the last 6 months.
Use this if you need to combine infrared and visible light images into a single, enhanced image that can withstand deliberate attempts to confuse computer vision systems.
Not ideal if you are looking for a general-purpose image fusion tool without a specific need for defense against adversarial attacks, or if you only work with single-modality images.
Stars
31
Forks
1
Language
Python
License
MIT
Category
Last pushed
Oct 10, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/lok-18/A2RNet"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
deepinv/deepinv
DeepInverse: a PyTorch library for solving imaging inverse problems using deep learning
fidler-lab/polyrnn-pp
Inference Code for Polygon-RNN++ (CVPR 2018)
mhamilton723/STEGO
Unsupervised Semantic Segmentation by Distilling Feature Correspondences
yjxiong/tsn-pytorch
Temporal Segment Networks (TSN) in PyTorch
pyxu-org/pyxu
Modular and scalable computational imaging in Python with GPU/out-of-core computing.