3 papers
cs.CV2026
HazeSpikeMamba: Coupling Spiking-Inspired and State-Space Features for Self-Supervised Real-World Dehazing
Haoran Liu, Huibin Li, Mingzhe Liu +2
Dehazing networks are commonly trained on synthetic hazy-clear pairs, but their performance often drops on real photographs. Synthetic haze generated using the atmospheric scatteri…
cs.CV2026
Ranking Image Fusion the Way Humans Do: A Learned Pairwise Preference Measure for Infrared-Visible Fusion Assessment
Haoran Liu, Mingzhe Liu, Peng Li +1
Infrared-visible image fusion (IVIF) has no ideal fused reference, so algorithms are ranked by scalar objective metrics that formalize proxies for information transfer, structure,…
cs.CV2025
U-Net-Like Spiking Neural Networks for Single Image Dehazing
Huibin Li, Haoran Liu, Mingzhe Liu +3
Image dehazing is a critical challenge in computer vision, essential for enhancing image clarity in hazy conditions. Traditional methods often rely on atmospheric scattering models…