
MambaDFuse, a novel Mamba-based model, effectively and efficiently integrates complementary information from different modalities to generate high-quality fused images that enhance scene representation and facilitate downstream visual tasks.


coremsg

mamba-based-dual-phase-model-for-effective-and-efficient-multi-modality-image-fusion


Mamba-based Dual-phase Model for Effective and Efficient Multi-modality Image Fusion


title_rewrite


DAE-Fuse, a novel two-phase discriminative autoencoder framework, generates sharp and natural fused images by introducing adversarial feature extraction and attention-guided cross-modality fusion.


dae-fuse-a-discriminative-autoencoder-for-generating-sharp-and-natural-multi-modality-fused-images


DAE-Fuse: A Discriminative Autoencoder for Generating Sharp and Natural Multi-Modality Fused Images
