Learning from Failure: Leveraging Unreliable Predictions in Semi-Supervised Real-World Adverse Weather Removal

arXiv:2610.02051 · cs.CV · Submitted 2026-10-01 · Read on arXiv

cs.CV

Submitted: 2026-10-01

Updated: 2026-10-01

Terminology

• Consistency — 15× in this paper · explained in 3 episodes
• Computer Vision and Pattern Recognition — 14× in this paper
• Semi-supervised Learning — 9× in this paper · explained in 4 episodes
• Transformer — 9× in this paper · explained in 2 episodes
• Ablation — 6× in this paper · explained in 1 episode
• Generalization — 6× in this paper · explained in 13 episodes
• Benchmark — 5× in this paper · explained in 2 episodes
• Ablation Studies — 4× in this paper · explained in 1 episode
• Computational overhead — 4× in this paper · explained in 2 episodes
• Contrastive Learning — 4× in this paper · explained in 5 episodes
• Generative AI — 4× in this paper · explained in 2 episodes
• Reinforcement Learning — 3× in this paper · explained in 4 episodes
• Adam — 2× in this paper · explained in 2 episodes
• Downstream Tasks — 2× in this paper · explained in 2 episodes
• Fidelity — 2× in this paper · explained in 2 episodes
• Ablation study — 1× in this paper · explained in 1 episode
• Accuracy — 1× in this paper · explained in 1 episode
• Adaptability — 1× in this paper · explained in 1 episode
• Adaptive Strategy — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• Attention Mechanism — 1× in this paper · explained in 2 episodes
• Benchmarking — 1× in this paper · explained in 3 episodes
• Diffusion Model — 1× in this paper · explained in 8 episodes
• Exponential Moving Average (EMA) — 1× in this paper · explained in 2 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• IEEE International Conference on Computer Vision — 1× in this paper
• Loss Function — 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
• Structural Constraints — 1× in this paper · explained in 2 episodes
• Synthetic Data Generation — 1× in this paper · explained in 5 episodes
• Transfer Learning — 1× in this paper · explained in 10 episodes
• Vision-Language Models (VLMs) — 1× in this paper · explained in 6 episodes

Sources

• FD-GAN: Generative Adversarial Networks with Fusion-discriminator for Single Image Dehazing
• Adam: A Method for Stochastic Optimization
• PromptIR: Prompting for All-in-One Blind Image Restoration
• Very Deep Convolutional Networks for Large-Scale Image Recognition
• Understanding the performance gap between online and offline alignment algorithms
• YOLOv12: Attention-Centric Real-Time Object Detectors
• Q-Align: Teaching LMMs for Visual Scoring via Discrete Text-Defined Levels

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