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Cross Modal Retrieval On Rsitmd

Metrics

Image-to-text R@1
Mean Recall
text-to-imageR@1

Results

Performance results of various models on this benchmark

Paper Title
HarMA (w/ GeoRSCLIP)32.74%52.27%25.62%Efficient Remote Sensing with Harmonized Transfer Learning and Modality Alignment
GeoRSCLIP-FT32.30%51.81%25.04%RS5M and GeoRSCLIP: A Large Scale Vision-Language Dataset and A Large Vision-Language Model for Remote Sensing
GLISA32.08%50.69%23.36%Global–Local Information Soft-Alignment for Cross-Modal Remote-Sensing Image–Text Retrieval
RemoteCLIP28.76%50.52%23.76%RemoteCLIP: A Vision Language Foundation Model for Remote Sensing
PE-RSITR (MRS-Adapter)23.67%44.47%20.10%Parameter-Efficient Transfer Learning for Remote Sensing Image-Text Retrieval
PIR18.14%38.24%12.17%A Prior Instruction Representation Framework for Remote Sensing Image-text Retrieval
DOVE16.81%37.73%12.20%Direction-Oriented Visual-semantic Embedding Model for Remote Sensing Image-text Retrieval
GaLR14.82%31.41%11.15%Remote Sensing Cross-Modal Text-Image Retrieval Based on Global and Local Information
SWAN13.35%34.11%11.24%Reducing Semantic Confusion: Scene-aware Aggregation Network for Remote Sensing Cross-modal Retrieval
AMFMN10.63%29.72%11.51%Exploring a Fine-Grained Multiscale Method for Cross-Modal Remote Sensing Image Retrieval
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Cross Modal Retrieval On Rsitmd | SOTA | HyperAI