SAMatcher: Dense Co-Visibility Modeling via Cross-View Fusion for Scale-Imbalance Image Matching

arXiv:2606.03406 · cs.CV · Submitted 2026-06-02 · Read on arXiv

cs.CV

Submitted: 2026-06-02

Updated: 2026-09-22

Terminology

• Consistency — 24× in this paper · explained in 3 episodes
• Transformer — 18× in this paper · explained in 2 episodes
• Accuracy — 10× in this paper · explained in 1 episode
• Robustness — 10× in this paper · explained in 5 episodes
• AUC — 9× in this paper · explained in 2 episodes
• Alignment — 8× in this paper · explained in 1 episode
• Ablation — 5× in this paper · explained in 1 episode
• Benchmark — 4× in this paper · explained in 2 episodes
• Foundation Model — 4× in this paper · explained in 3 episodes
• Generalization — 4× in this paper · explained in 13 episodes
• Segment Anything Model — 4× in this paper
• Abstraction — 3× in this paper · explained in 1 episode
• Core — 3× in this paper · explained in 2 episodes
• Embeddings — 3× in this paper · explained in 2 episodes
• Foundation Models — 3× in this paper · explained in 7 episodes
• Regularization — 3× in this paper · explained in 3 episodes
• Representation Learning — 3× in this paper · explained in 2 episodes
• Semantic Alignment — 3× in this paper · explained in 3 episodes
• Ablation Studies — 2× in this paper · explained in 1 episode
• Domain Shift — 2× in this paper · explained in 4 episodes
• Feature Extraction — 2× in this paper · explained in 2 episodes
• Nearest Neighbor — 2× in this paper
• Segment Anything Model (SAM) — 2× in this paper · explained in 2 episodes
• Zero-Shot Generalization — 2× in this paper · explained in 5 episodes
• Ablation study — 1× in this paper · explained in 1 episode
• AdamW Optimizer — 1× in this paper · explained in 1 episode
• Aggregation — 1× in this paper · explained in 1 episode
• Area Under the Curve — 1× in this paper
• Attention Mechanism — 1× in this paper · explained in 3 episodes
• Diffusion Model — 1× in this paper · explained in 8 episodes
• Diffusion Models — 1× in this paper · explained in 6 episodes
• Downstream Tasks — 1× in this paper · explained in 2 episodes
• Failure Modes — 1× in this paper · explained in 3 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Instance Segmentation — 1× in this paper · explained in 3 episodes
• Interpretability — 1× in this paper · explained in 15 episodes
• Matching Score — 1× in this paper
• Point Clouds — 1× in this paper · explained in 2 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Unified Framework — 1× in this paper · explained in 5 episodes
• Verification — 1× in this paper · explained in 2 episodes

Sources

• SA-VLA: Spatially-Aware Flow-Matching for Vision-Language-Action Reinforcement Learning
• SAM 2: Segment Anything in Images and Videos

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