Semi-LAR is a semi-supervised contrastive learning framework with linear attention for nighttime flare removal that refines pseudo-labels via quality assessment and uses flare-aware patch-level contrastive losses.
For overall nighttime visibility: Integrate irregular glow removal with glow-aware enhancement
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Semi-LAR: Semi-supervised Contrastive Learning with Linear Attention for Removal of Nighttime Flares
Semi-LAR is a semi-supervised contrastive learning framework with linear attention for nighttime flare removal that refines pseudo-labels via quality assessment and uses flare-aware patch-level contrastive losses.