S3VD: Semantic-Guidance Spatio-Temporal Scanning for Video Deraining

arXiv:2609.21322 · cs.CV · Submitted 2026-09-18 · Read on arXiv

cs.CV

Submitted: 2026-09-18

Updated: 2026-09-18

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Ablation — 20× in this paper · explained in 1 episode
• Consistency — 10× in this paper · explained in 3 episodes
• Robustness — 10× in this paper · explained in 5 episodes
• Multi-Scale Semantic Fusion — 9× in this paper
• Transformer — 9× in this paper · explained in 2 episodes
• Alignment — 7× in this paper · explained in 1 episode
• Core — 6× in this paper · explained in 2 episodes
• Spatio-Temporal Scanning Fusion — 6× in this paper
• Feature Extraction — 5× in this paper · explained in 2 episodes
• Foundation Model — 5× in this paper · explained in 3 episodes
• Temporal Mamba Block — 5× in this paper
• Benchmark — 4× in this paper · explained in 2 episodes
• Fidelity — 4× in this paper · explained in 2 episodes
• Spatial Mamba Block — 4× in this paper
• Temporal Correlations — 4× in this paper · explained in 2 episodes
• Foundation Models — 3× in this paper · explained in 7 episodes
• Generalization — 3× in this paper · explained in 13 episodes
• Loss Function — 3× in this paper · explained in 2 episodes
• Temporal consistency — 3× in this paper · explained in 2 episodes
• Ablation Studies — 2× in this paper · explained in 1 episode
• Ablation study — 2× in this paper · explained in 1 episode
• Accuracy — 2× in this paper · explained in 1 episode
• Adaptability — 2× in this paper · explained in 1 episode
• Aggregation — 2× in this paper · explained in 1 episode
• Attention Mechanism — 2× in this paper · explained in 2 episodes
• Convolutional Neural Networks (CNNs) — 2× in this paper · explained in 2 episodes
• Cosine Similarity — 2× in this paper · explained in 3 episodes
• Regularization — 2× in this paper · explained in 3 episodes
• Representation Learning — 2× in this paper · explained in 2 episodes
• Semantic Understanding — 2× in this paper · explained in 2 episodes
• State Space Models (SSMs) — 2× in this paper · explained in 4 episodes
• Abstraction — 1× in this paper · explained in 1 episode
• Adam — 1× in this paper · explained in 2 episodes
• Adaptation — 1× in this paper · explained in 1 episode
• Contrastive Learning — 1× in this paper · explained in 5 episodes
• Cross-Attention Mechanism — 1× in this paper · explained in 2 episodes
• Downstream Tasks — 1× in this paper · explained in 2 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Feature Selection — 1× in this paper · explained in 4 episodes
• Optical Flow — 1× in this paper · explained in 2 episodes
• Peak Signal-to-Noise Ratio — 1× in this paper
• RAFT-based Warp Error — 1× in this paper
• Redundancy — 1× in this paper · explained in 2 episodes
• Sparsity — 1× in this paper · explained in 4 episodes
• Structural Integrity — 1× in this paper · explained in 3 episodes
• Zero-Shot Transfer — 1× in this paper · explained in 4 episodes

Sources

• Mamba: Linear-Time Sequence Modeling with Selective State Spaces
• Multi-task Image Restoration Guided By Robust DINO Features
• A Unified Low-level Foundation Model for Enhancing Pathology Image Quality
• DeLiVR: Differential Spatiotemporal Lie Bias for Efficient Video Deraining

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