Popular GitHub Repositories for Infrared

LLVIP: A Visible-infrared Paired Dataset for Low-light Vision

[MIR-2023-Survey] A continuously updated paper list for multi-modal pre-trained big models

CVPR 2022 | Target-aware Dual Adversarial Learning and a Multi-scenario Multi-Modality Benchmark to Fuse Infrared and Visible for Object Detection.

BERT, AWS RDS, AWS Forecast, EMR Spark Cluster, Hive, Serverless, Google Assistant + Raspberry Pi, Infrared, Google Cloud Platform Natural Language, Anomaly detection, Tensorflow, Mathematics

Transformer-based fNIRS Classification. Paper: Transformer Model for Functional Near-Infrared Spectroscopy Classification

[IEEE TCSVT 2023] Official implementation of DATFuse: Infrared and Visible Image Fusion via Dual Attention Transformer

CM-NAS: Cross-Modality Neural Architecture Search for Visible-Infrared Person Re-Identification (ICCV2021)

[IEEE TMM 2022] Official implementation of YDTR: Infrared and Visible Image Fusion via Y-shape Dynamic Transformer

Official implementation of the paper "Maximizing Self-supervision from Thermal Image for Effective Self-supervised Learning of Depth and Ego-motion"

Code for the paper 'Skin Segmentation from NIR Images using Unsupervised Domain Adaptation through Generative Latent Search'. Accepted in ECCV2020 (Spotlight). Preprint: https://arxiv.org/abs/2006.08696

Training for multi-modal image fusion with PyTorch.

Implementation of the FIRe-GAN model, a GAN-based method for the fusion of visible-infrared images.

Low contrast infrared image enhancement with DCGAN

[ECCV2024] ModTr: Modality Translation for Object Detection Adaptation Without Forgetting Prior Knowledge

AAAI 2025 | A2RNet: Adversarial Attack Resilient Network for Robust Infrared and Visible Image Fusion

Neural Networks and Deep Learning Course Project

Multimodal & infrared automotive dataset. Published at WACV 2024 (Oral).

This repository contains the implementation of an advanced machine learning system for detecting anomalies in PCB components. The system uses infrared imaging to identify and mark overheated or faulty components, ensuring efficient and accurate fault detection.

The use of ultraviolet light, infrared and magnetic field one can detect the existence of counterfeit money. Unfortunately, such advanced technology is costly. Therefore, another simple method is needed. One of solutions is using digital image processing technique. Edge detection technique by canny method able to detect the presence of watermarks that are often used to detect the authenticity of banknotes

[JOLT 2025] Official implementation of Rethinking the Approach to Lightweight Multi-Branch Heterogeneous Image Fusion Frameworks: Infrared and Visible Image Fusion via the Parallel Mamba-KAN Framework