Exploring the Potential of Contrastive Language-Image Pre-training for Multi-Source Remote Sensing Data

arXiv:2609.03391 · cs.CV, cs.AI · Submitted 2026-09-03 · Read on arXiv

cs.CV, cs.AI

Submitted: 2026-09-03

Updated: 2026-09-16

Terminology

• Alignment — 25× in this paper · explained in 1 episode
• Contrastive Learning — 13× in this paper · explained in 5 episodes
• Adaptation — 10× in this paper · explained in 1 episode
• Ablation — 5× in this paper · explained in 1 episode
• Feature Selection — 5× in this paper · explained in 4 episodes
• Foundation Model — 5× in this paper · explained in 3 episodes
• Benchmark — 4× in this paper · explained in 2 episodes
• Core — 4× in this paper · explained in 2 episodes
• Distillation — 4× in this paper · explained in 2 episodes
• Embeddings — 4× in this paper · explained in 2 episodes
• Transferability — 3× in this paper · explained in 4 episodes
• Transformer — 3× in this paper · explained in 2 episodes
• Ablation study — 2× in this paper · explained in 1 episode
• Consistency — 2× in this paper · explained in 3 episodes
• Grounding — 2× in this paper · explained in 3 episodes
• Semantic Alignment — 2× in this paper · explained in 3 episodes
• Spectral-Spatial Basis Decomposition — 2× in this paper
• Ablation Studies — 1× in this paper · explained in 1 episode
• Accuracy — 1× in this paper · explained in 1 episode
• Activation Function — 1× in this paper · explained in 1 episode
• Cosine Similarity — 1× in this paper · explained in 3 episodes
• Representation Learning — 1× in this paper · explained in 2 episodes
• Semantic Understanding — 1× in this paper · explained in 2 episodes
• Spectral Gap — 1× in this paper · explained in 5 episodes
• Two-Stage Training Strategy — 1× in this paper · explained in 3 episodes
• Two-stage training — 1× in this paper · explained in 2 episodes
• Unified Framework — 1× in this paper · explained in 5 episodes

Sources

• SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features
• Neural Plasticity-Inspired Multimodal Foundation Model for Earth Observation
• GeoAlignCLIP: Enhancing Fine-Grained Vision-Language Alignment in Remote Sensing via Multi-Granular Consistency Learning

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