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.

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

CAVER: Cross-Modal View-Mixed Transformer for Bi-Modal Salient Object Detection

Alignment-Free RGBT Salient Object Detection: Semantics-guided Asymmetric Correlation Network and A Unified Benchmark

Unified-modal Salient Object Detection via Adaptive Prompt Learning

Learning Adaptive Fusion Bank for Multi-modal Salient Object Detection

Alignment-Free RGB-T Salient Object Detection: A Large-scale Dataset and Progressive Correlation Network

ComPtr: Towards Diverse Bi-source Dense Prediction Tasks via A Simple yet General Complementary Transformer (TPAMI 2025)