RSPrompter: Learning to prompt for remote sensing instance segmentation based on visual foundation model
Leveraging the extensive training data from SA-1B, the segment anything model (SAM)
demonstrates remarkable generalization and zero-shot capabilities. However, as a category …
demonstrates remarkable generalization and zero-shot capabilities. However, as a category …
Change-agent: Towards interactive comprehensive remote sensing change interpretation and analysis
Monitoring changes in the Earth's surface is crucial for understanding natural processes and
human impacts, necessitating precise and comprehensive interpretation methodologies …
human impacts, necessitating precise and comprehensive interpretation methodologies …
Semantic-cc: Boosting remote sensing image change captioning via foundational knowledge and semantic guidance
Remote sensing image change captioning (RSICC) aims to articulate the changes in objects
of interest within bitemporal remote sensing images using natural language. Given the …
of interest within bitemporal remote sensing images using natural language. Given the …
Remote Sensing Temporal Vision-Language Models: A Comprehensive Survey
Temporal image analysis in remote sensing has traditionally centered on change detection,
which identifies regions of change between images captured at different times. However …
which identifies regions of change between images captured at different times. However …
[HTML][HTML] A Review of Deep Learning-Based Remote Sensing Image Caption: Methods, Models, Comparisons and Future Directions
K Zhang, P Li, J Wang - Remote Sensing, 2024 - mdpi.com
Remote sensing images contain a wealth of Earth-observation information. Efficient
extraction and application of hidden knowledge from these images will greatly promote the …
extraction and application of hidden knowledge from these images will greatly promote the …
Ringmogpt: A unified remote sensing foundation model for vision, language, and grounded tasks
Recently, multi-modal large language models (MLLMs) have shown excellent reasoning
capabilities in various fields. Most of the existing remote sensing MLLMs solve image-level …
capabilities in various fields. Most of the existing remote sensing MLLMs solve image-level …
Ccexpert: Advancing mllm capability in remote sensing change captioning with difference-aware integration and a foundational dataset
Z Wang, M Wang, S Xu, Y Li, B Zhang - arxiv preprint arxiv:2411.11360, 2024 - arxiv.org
Remote Sensing Image Change Captioning (RSICC) aims to generate natural language
descriptions of surface changes between multi-temporal remote sensing images, detailing …
descriptions of surface changes between multi-temporal remote sensing images, detailing …
Mv-cc: Mask enhanced video model for remote sensing change caption
Remote sensing image change caption (RSICC) aims to provide natural language
descriptions for bi-temporal remote sensing images. Since Change Caption (CC) task …
descriptions for bi-temporal remote sensing images. Since Change Caption (CC) task …
[HTML][HTML] Dual-Branch Seasonal Error Elimination Change Detection Framework Using Target Image Feature Fusion Generator
In change detection tasks, seasonal variations in spectral characteristics and surface cover
can negatively impact performance when comparing image pairs from different seasons …
can negatively impact performance when comparing image pairs from different seasons …
Efficient Semantic Splatting for Remote Sensing Multi-view Segmentation
In this paper, we propose a novel semantic splatting approach based on Gaussian Splatting
to achieve efficient and low-latency. Our method projects the RGB attributes and semantic …
to achieve efficient and low-latency. Our method projects the RGB attributes and semantic …