FLVRS25
* *Workshop on Foundation and Large Vision Models in Remote Sensing
* Bridging the Modality Gap: Training-Free Adaptation of Vision-Language Models for Remote Sensing via Visual Prototypes
* COP-GEN-Beta: Unified Generative Modelling of COPernicus Imagery Thumbnails
* Deep Diffusion Models and Unsupervised Hyperspectral Unmixing for Realistic Abundance Map Synthesis
* Dynamic State-Control Modeling for Generalized Remote Sensing Image Super-Resolution
* Efficient Self-Supervised Learning for Earth Observation via Dynamic Dataset Curation
* Foundation Models for Remote Sensing: An Analysis of MLLMs for Object Localization
* MESA: Text-Driven Terrain Generation Using Latent Diffusion and Global Copernicus Data
* Pan-Rsvqa: Vision Foundation Models as Pseudo-Annotators for Remote Sensing Visual Question Answering
* Sensor Agnostic Domain Generalization Framework for Leveraging Geospatial Foundation Models: Enhancing Semantic Segmentation via Synergistic Pseudo-Labeling and Generative Learning, A
* Towards Efficient Benchmarking of Foundation Models in Remote Sensing: A Capabilities Encoding Approach
11 for FLVRS25