Learning Where and What to Restore for Composite Image Restoration

arXiv:2503.17915 · eess.IV, cs.AI, cs.CV, cs.LG · Submitted 2025-03-23 · Read on arXiv

eess.IV, cs.AI, cs.CV, cs.LG

Submitted: 2025-03-23

Updated: 2026-09-27

Project page: https://kongwanbianjinyu.github.io/Cat-AIR/PSNR

Terminology

• Transformer — 17× in this paper · explained in 2 episodes
• Attention Mechanism — 16× in this paper · explained in 3 episodes
• Conference on Computer Vision and Pattern Recognition — 10× in this paper
• Ablation — 6× in this paper · explained in 1 episode
• Adaptability — 4× in this paper · explained in 1 episode
• Core — 4× in this paper · explained in 2 episodes
• Fine-Tuning — 4× in this paper · explained in 5 episodes
• Adaptation — 3× in this paper · explained in 1 episode
• Benchmark — 3× in this paper · explained in 2 episodes
• Exponential Moving Average — 3× in this paper
• Ablation Studies — 2× in this paper · explained in 1 episode
• Computational overhead — 2× in this paper · explained in 2 episodes
• Fidelity — 2× in this paper · explained in 2 episodes
• Inverse Problem — 2× in this paper · explained in 2 episodes
• Ablation study — 1× in this paper · explained in 1 episode
• Adaptive Mechanism — 1× in this paper · explained in 1 episode
• Benchmarking — 1× in this paper · explained in 3 episodes
• Contrastive Learning — 1× in this paper · explained in 5 episodes
• Decoupled Learning — 1× in this paper · explained in 2 episodes
• Diffusion Model — 1× in this paper · explained in 8 episodes
• Diffusion Models — 1× in this paper · explained in 6 episodes
• Exponential Moving Average (EMA) — 1× in this paper · explained in 2 episodes
• Generalizability — 1× in this paper · explained in 6 episodes
• Hybrid Approach — 1× in this paper · explained in 4 episodes
• Latent Representation — 1× in this paper · explained in 2 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• Meta-learning — 1× in this paper · explained in 2 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Unified Framework — 1× in this paper · explained in 5 episodes

Sources

• A Comparative Study of Image Restoration Networks for General Backbone Network Design
• Always Clear Days: Degradation Type and Severity Aware All-In-One Adverse Weather Removal
• Categorical Reparameterization with Gumbel-Softmax
• Instruct-IPT: All-in-One Image Processing Transformer via Weight Modulation
• Uformer: A General U-Shaped Transformer for Image Restoration
• Deep Retinex Decomposition for Low-Light Enhancement
• Unified-Width Adaptive Dynamic Network for All-In-One Image Restoration

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