From Change Captions to Change Detection: Semantic-Appearance Agreement Framework for Remote Sensing Change Detection

arXiv:2609.28192 · cs.CV · Submitted 2026-09-23 · Read on arXiv

cs.CV

Submitted: 2026-09-23

Updated: 2026-09-23

Code: https://github.com/qianyuancs/SAAF

Terminology

• Transformer — 8× in this paper · explained in 2 episodes
• Ablation — 7× in this paper · explained in 1 episode
• Computer Vision and Pattern Recognition — 7× in this paper
• Adaptation — 4× in this paper · explained in 1 episode
• Ablation Studies — 3× in this paper · explained in 1 episode
• Alignment — 3× in this paper · explained in 1 episode
• Representation Learning — 3× in this paper · explained in 2 episodes
• Semantic-Appearance Agreement Framework — 3× in this paper
• Accuracy — 2× in this paper · explained in 1 episode
• Consistency — 2× in this paper · explained in 3 episodes
• Diffusion Model — 2× in this paper · explained in 8 episodes
• Diffusion Models — 2× in this paper · explained in 6 episodes
• Domain Adaptation — 2× in this paper · explained in 5 episodes
• Foundation Model — 2× in this paper · explained in 3 episodes
• Semantic Alignment — 2× in this paper · explained in 3 episodes
• Contrastive Learning — 1× in this paper · explained in 5 episodes
• Distillation — 1× in this paper · explained in 2 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• European Conference on Computer Vision — 1× in this paper
• Fidelity — 1× in this paper · explained in 2 episodes
• Grounding — 1× in this paper · explained in 3 episodes
• International Conference on Learning Representations — 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
• Learned Perceptual Image Patch Similarity — 1× in this paper
• Mask Generation — 1× in this paper · explained in 2 episodes
• Nash Equilibrium — 1× in this paper · explained in 2 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Self-Supervised Learning — 1× in this paper · explained in 8 episodes

Sources

• Remote Sensing Image Change Detection with Transformers
• Language-driven Semantic Segmentation
• DenseCLIP: Language-Guided Dense Prediction with Context-Aware Prompting
• Image Segmentation Using Text and Image Prompts
• FLAIR #1: semantic segmentation and domain adaptation dataset
• Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

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