awesome-vision-language-models-for-earth-observation
github.com/geoaigroup/awesome-vision-language-models-for-earth-observation ↗A curated list of awesome vision and language resources for earth observation.
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Related Repositories & Libraries
Vision-Language Remote Sensing Datasets
- CapERA: Captioning Events in Aerial Videos
Size : 2864 videos and 14,320 captions, where each video is paired with five unique captions
- Change Detection-Based Visual Question Answering Dataset
Size: 2,968 pairs of multitemporal images and more than 122,000 question–answer pairs Classes: 6 Resolution : 512×512 pixels Platforms: It is based on semantic change detection dataset (SECOND) Use: Remote Sensing Visual Question Answering
- Dense Labeling Remote Sensing Dataset (DLRSD)
Size: 2,100 images Number of Classes: 21 Resolution : 256 x 256 Platforms: Extension of the UC Merced Use: Remote Sensing Image Retrieval (RSIR), Classification and Semantic Segmentation
- Dior-Remote Sensing Visual Grounding Dataset (RSVGD)
Size: 38,320 RS image-query pairs and 17,402 RS images Number of Classes: 20 Resolution : 800 x 800 Platforms: DIOR dataset Use: Remote Sensing Visual Grounding
- FloodNet Visual Question Answering Dataset
Size: 11,000 question-image pairs Resolution : 224 x 224 Platforms: UAV-DJI Mavic Pro quadcopters, after Hurricane Harvey Use: Remote Sensing Visual Question Answering
- LAION-EO
Size : 24,933 samples with 40.1% english captions as well as other common languages from LAION-5B mean height of 633.0 pixels (up to 9,999) and mean width of 843.7 pixels (up to 19,687) Platforms : Based on LAION-5B
Showing a sample of 27 resources. View the full list on GitHub →