Beate-Suy-Zhang/DCEvo

A summary of open-source deep learning-based infrared and visible image fusion and some vision algorithms. 红外与可见光图像融合的开源代码

Infrared and Visible Image Fusion: From Data Compatibility to Task Adaption. A fire-new survey for infrared and visible image fusion.

A collection of deep learning based RGB-T-Fusion methods, codes, and datasets. The main directions involved are Multispectral Pedestrian Detection, RGB-T Aerial Object Detection, RGB-T Semantic Segmentation, RGB-T Crowd Counting, RGB-T Fusion Tracking.

A toolbox for HSI-MSI fusion/pan-sharpening, including MoGDCN, Fusformer, PSRT, MSST, DCTransformer, iDaFormer, HySure, HyMS, DBSR, UDALN,uHNTC, PSTUN, UTAL, CaFormer and pretrained weights

RGB-T Fusion, RGB-T SOD, RGB-T Vehicle Detection, RGB-T Crowd Counting, RGB-T Pedestrian Detection, RGB-T Semantic Segmeantaion, RGB-T Tracking

[Accepted by ICCV2025] Official code of the paper "From Easy to Hard: Progressive Active Learning Framework for Infrared Small Target Detection with Single Point Supervision"

IRSAM:Advancing Segment Anything Model for Infrared Small Target Detection

A ready-to-use notebook!

[CVPR 2026] Multinex: Lightweight Low-light Image Enhancement via Multi-prior Retinex