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Found 7 papers, 2 papers with code
Simultaneous Tri-Modal Medical Image Fusion and Super-Resolution using Conditional Diffusion Model
In clinical practice, tri-modal medical image fusion, compared to the existing dual-modal technique, can provide a more comprehensive view of the lesions, aiding physicians in evaluating the disease's shape, location, and biological activity.
Decomposition-based and Interference Perception for Infrared and Visible Image Fusion in Complex Scenes
Infrared and visible image fusion has emerged as a prominent research in computer vision.
Physical Perception Network and an All-weather Multi-modality Benchmark for Adverse Weather Image Fusion
To bridge this research gap, we proposed an all-weather MMIF model.
TSJNet: A Multi-modality Target and Semantic Awareness Joint-driven Image Fusion Network
Multi-modality image fusion involves integrating complementary information from different modalities into a single image.
SAMF: Small-Area-Aware Multi-focus Image Fusion for Object Detection
Existing multi-focus image fusion (MFIF) methods often fail to preserve the uncertain transition region and detect small focus areas within large defocused regions accurately.
Bridging the Gap between Multi-focus and Multi-modal: A Focused Integration Framework for Multi-modal Image Fusion
However, the fusion of multiple visible images with different focal regions and infrared images is a unprecedented challenge in real MMIF applications.
ATPL: Mutually enhanced adversarial training and pseudo labeling for unsupervised domain adaptation
Accordingly, ATPL will use the pseudo-labeled information to improve the adversarial training process, which can guarantee the feature transferability by generating adversarial data to fill in the domain gap.
