3 citations · 6 across the 9 of their papers we have counts for
4 papers · 1 filter
Revisiting Generative Infrared and Visible Image Fusion Based on Human Cognitive Laws
Lin Guo, Xiaoqing Luo, Wei Xie +5
Existing infrared and visible image fusion methods often face the dilemma of balancing modal information. Generative fusion methods reconstruct fused images by learning from data d…
OCCO: LVM-guided Infrared and Visible Image Fusion Framework based on Object-aware and Contextual COntrastive Learning
Hui Li, Congcong Bian, Zeyang Zhang +3
Image fusion is a crucial technique in the field of computer vision, and its goal is to generate high-quality fused images and improve the performance of downstream tasks. However,…
One Model for ALL: Low-Level Task Interaction Is a Key to Task-Agnostic Image Fusion
Chunyang Cheng, Tianyang Xu, Zhenhua Feng +7
Advanced image fusion methods mostly prioritise high-level missions, where task interaction struggles with semantic gaps, requiring complex bridging mechanisms. In contrast, we pro…
One Latent Space to Rule All Degradations: Unifying Restoration Knowledge for Image Fusion
Haolong Ma, Hui Li, Chunyang Cheng +4
All-in-One Degradation-Aware Fusion Models (ADFMs) as one of multi-modal image fusion models, which aims to address complex scenes by mitigating degradations from source images and…