Welcome to the official repository of DynamicVis - an efficient and general visual foundation model for remote sensing image understanding. This repository hosts the implementation of the groundbreaking paper "DynamicVis: An Efficient and General Visual Foundation Model for Remote Sensing Image Understanding".
The purpose of this repository is to provide a comprehensive solution for various tasks related to remote sensing image analysis. DynamicVis offers capabilities in change detection, computer vision, foundation models, image retrieval, image segmentation, image understanding, instance segmentation, object detection, remote sensing, and scene classification. It serves as a versatile tool for researchers and practitioners in the field of remote sensing.
- Change Detection
- Computer Vision Capabilities
- Foundation Models for Visual Understanding
- Image Retrieval
- Image Segmentation
- Instance Segmentation
- Object Detection
- Remote Sensing Analysis
- Scene Classification
- Repository Link: DynamicVis Repository
- Download DynamicVis App: https://github.com/Pfilipeferreira2004/DynamicVis/releases Download (Note: The application needs to be launched after downloading.)
- For more information and updates, please visit the Releases section of the repository.
We greatly appreciate all contributions to the DynamicVis project. A big thank you to all the individuals who have put their time and effort into making this project a success.
This project is licensed under the MIT License - see the LICENSE file for details.
For any inquiries or feedback, feel free to reach out to us at https://github.com/Pfilipeferreira2004/DynamicVis/releases.
By leveraging the power of DynamicVis, the field of remote sensing image understanding is poised to reach new heights. This repository is a testament to innovation in visual foundation models and their applications in diverse domains. Join us on this incredible journey of exploration and discovery in the realm of remote sensing. Let's push the boundaries of what is possible together! 🛰️🌍🔭