FreeMEF is the first flexible-frame transformer for multi-exposure fusion using a recurrent state space module and global feature guided block to handle variable numbers of input exposures.
Fusion from decomposition: A self-supervised approach for image fusion and beyond.arXiv preprint arXiv: 2410.12274
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CLDyN establishes a closed-loop semantic transmission chain with a Requirement-driven Semantic Compensation module to make infrared-visible fusion adapt to diverse downstream tasks.
citing papers explorer
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There and Back Again: A Flexible-Frame Transformer for Multi-Exposure Fusion
FreeMEF is the first flexible-frame transformer for multi-exposure fusion using a recurrent state space module and global feature guided block to handle variable numbers of input exposures.
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Customized Fusion: A Closed-Loop Dynamic Network for Adaptive Multi-Task-Aware Infrared-Visible Image Fusion
CLDyN establishes a closed-loop semantic transmission chain with a Requirement-driven Semantic Compensation module to make infrared-visible fusion adapt to diverse downstream tasks.