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Found 5 papers, 5 papers with code
Multi-interactive Feature Learning and a Full-time Multi-modality Benchmark for Image Fusion and Segmentation
Multi-modality image fusion and segmentation play a vital role in autonomous driving and robotic operation.
Ranked #3 on
Semantic Segmentation
on FMB Dataset
Embracing Compact and Robust Architectures for Multi-Exposure Image Fusion
In recent years, deep learning-based methods have achieved remarkable progress in multi-exposure image fusion.
Bi-level Dynamic Learning for Jointly Multi-modality Image Fusion and Beyond
Recently, multi-modality scene perception tasks, e. g., image fusion and scene understanding, have attracted widespread attention for intelligent vision systems.
CoCoNet: Coupled Contrastive Learning Network with Multi-level Feature Ensemble for Multi-modality Image Fusion
Infrared and visible image fusion targets to provide an informative image by combining complementary information from different sensors.
Target-aware Dual Adversarial Learning and a Multi-scenario Multi-Modality Benchmark to Fuse Infrared and Visible for Object Detection
This study addresses the issue of fusing infrared and visible images that appear differently for object detection.
Ranked #1 on
Object Detection
on Multispectral Dataset
