Semi-LAR: Semi-supervised Contrastive Learning with Linear Attention for Removal of Nighttime Flares

arXiv:2605.18156 · cs.CV · Submitted 2026-05-18 · Read on arXiv

cs.CV

Submitted: 2026-05-18

Updated: 2026-09-17

Code: https://github.com/copr-sans/Semi-LAR

Terminology

• Contrastive Learning — 26× in this paper · explained in 5 episodes
• Consistency — 13× in this paper · explained in 3 episodes
• Transformer — 13× in this paper · explained in 2 episodes
• Regularization — 10× in this paper · explained in 3 episodes
• Robustness — 10× in this paper · explained in 5 episodes
• Benchmark — 8× in this paper · explained in 2 episodes
• Semi-supervised Learning — 7× in this paper · explained in 4 episodes
• Ablation — 6× in this paper · explained in 1 episode
• Generalization — 6× in this paper · explained in 13 episodes
• Channel Attention Block — 4× in this paper
• Representation Learning — 4× in this paper · explained in 2 episodes
• Ablation study — 3× in this paper · explained in 1 episode
• Model-Agnostic — 3× in this paper · explained in 2 episodes
• Ablation Studies — 2× in this paper · explained in 1 episode
• Adam — 2× in this paper · explained in 2 episodes
• Adaptation — 2× in this paper · explained in 1 episode
• Core — 2× in this paper · explained in 2 episodes
• Data Augmentation — 2× in this paper · explained in 7 episodes
• Directionally-Enhanced Spatial Module — 2× in this paper
• Entanglement — 2× in this paper · explained in 4 episodes
• Fidelity — 2× in this paper · explained in 2 episodes
• Over-smoothing — 2× in this paper · explained in 4 episodes
• Abundance — 1× in this paper · explained in 1 episode
• Accuracy — 1× in this paper · explained in 1 episode
• Aggregation — 1× in this paper · explained in 1 episode
• Aperture — 1× in this paper · explained in 1 episode
• Computational overhead — 1× in this paper · explained in 2 episodes
• Cosine Similarity — 1× in this paper · explained in 3 episodes
• Exponential Moving Average (EMA) — 1× in this paper · explained in 2 episodes
• Feature Extraction — 1× in this paper · explained in 2 episodes
• Iterative Refinement — 1× in this paper · explained in 3 episodes
• Pseudo-labeling — 1× in this paper · explained in 3 episodes
• Pseudo-labels — 1× in this paper · explained in 2 episodes
• Sparsity — 1× in this paper · explained in 4 episodes
• Transformer Architecture — 1× in this paper · explained in 2 episodes
• Update of Dependable Repository — 1× in this paper

Sources

• Toward Real Flare Removal: A Comprehensive Pipeline and A New Benchmark
• FlareX: A Physics-Informed Dataset for Lens Flare Removal via 2D Synthesis and 3D Rendering
• DFDNet: Dynamic Frequency-Guided De-Flare Network
• SLCFormer: Spectral-Local Context Transformer with Physics-Grounded Flare Synthesis for Nighttime Flare Removal

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