4 papers
Every SAM Drop Counts: Embracing Semantic Priors for Multi-Modality Image Fusion and Beyond
Guanyao Wu, Haoyu Liu, Hongming Fu +4
Multi-modality image fusion, particularly infrared and visible, plays a crucial role in integrating diverse modalities to enhance scene understanding. Although early research prior…
Infrared and Visible Image Fusion: From Data Compatibility to Task Adaption
Jinyuan Liu, Guanyao Wu, Zhu Liu +6
Infrared-visible image fusion (IVIF) is a critical task in computer vision, aimed at integrating the unique features of both infrared and visible spectra into a unified representat…
CoCoNet: Coupled Contrastive Learning Network with Multi-level Feature Ensemble for Multi-modality Image Fusion
Jinyuan Liu, Runjia Lin, Guanyao Wu +3
Infrared and visible image fusion targets to provide an informative image by combining complementary information from different sensors. Existing learning-based fusion approaches a…
Searching a Compact Architecture for Robust Multi-Exposure Image Fusion
Zhu Liu, Jinyuan Liu, Guanyao Wu +3
In recent years, learning-based methods have achieved significant advancements in multi-exposure image fusion. However, two major stumbling blocks hinder the development, including…