Learning Polarization Image Restoration with General Restoration Priors

arXiv:2609.30728 · cs.CV, eess.IV · Submitted 2026-09-25 · Read on arXiv

cs.CV, eess.IV

Submitted: 2026-09-25

Updated: 2026-09-25

Terminology

• Ablation — 8× in this paper · explained in 1 episode
• Transformer — 8× in this paper · explained in 2 episodes
• Computer Vision and Pattern Recognition — 7× in this paper
• Diffusion Model — 6× in this paper · explained in 8 episodes
• Ablation study — 4× in this paper · explained in 1 episode
• Benchmark — 4× in this paper · explained in 2 episodes
• Embeddings — 4× in this paper · explained in 2 episodes
• Fidelity — 4× in this paper · explained in 2 episodes
• Decoupling — 3× in this paper · explained in 2 episodes
• Diffusion Models — 3× in this paper · explained in 6 episodes
• In European Conference on Computer Vision — 3× in this paper
• Loss Function — 3× in this paper · explained in 2 episodes
• Ablation Studies — 2× in this paper · explained in 1 episode
• Accuracy — 2× in this paper · explained in 1 episode
• Adam — 2× in this paper · explained in 2 episodes
• Aggregation — 2× in this paper · explained in 1 episode
• Computational overhead — 2× in this paper · explained in 2 episodes
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• Generalization — 2× in this paper · explained in 13 episodes
• In International Conference on Learning Representations — 2× in this paper
• Activation Function — 1× in this paper · explained in 1 episode
• Adaptation — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• Angular Error — 1× in this paper · explained in 1 episode
• Downstream Tasks — 1× in this paper · explained in 2 episodes
• Feature Extraction — 1× in this paper · explained in 2 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• IEEE International Conference on Image Processing — 1× in this paper
• Latent Diffusion Model — 1× in this paper · explained in 2 episodes
• Latent Diffusion Models — 1× in this paper · explained in 2 episodes
• Mixture-of-Experts (MoE) — 1× in this paper · explained in 7 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• U-net architecture — 1× in this paper · explained in 3 episodes

Sources

• Adam: A Method for Stochastic Optimization
• PolarVSR: A Unified Framework and Benchmark for Continuous Space-Time Polarization Video Reconstruction
• SGDR: Stochastic Gradient Descent with Warm Restarts
• Stokes-Informed Diffusion for Robust Linear Polarization Estimation
• PolarAPP: Beyond Polarization Demosaicking for Polarimetric Applications
• Architectural Unification for Polarimetric Imaging Across Multiple Degradations

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