ChangeOS: Building damage assessment via Deep Object-based Semantic Change Detection - (RSE 2021)

A crop-agnostic model for estimating growth stage from an NDVI time series

AI Model Zoo for STM32 devices

OpenEarthMap-SAR: A benchmark dataset for land cover mapping under all-weather conditions

Annotation-Free Open-Vocabulary Segmentation for Remote-Sensing Images

[CVPR 2025 Oral] SegEarth-OV: Towards Training-Free Open-Vocabulary Segmentation for Remote Sensing Images

[ICLR 2026] Sat3DGen: Comprehensive Street-Level 3D Scene Generation from Single Satellite Image

[CVPR26] TESSERA is a foundation model that can process time-series satellite imagery for applications such as land classification and canopy height prediction. Developed at the University of Cambr…

[IEEE TIP 2021] Iterative Robust Graph for Unsupervised Change Detection of Heterogeneous Remote Sensing Images

[ISPRS P&RS 2025] Rules-Induced Energy Model (RIEM) for Multimodal Change Detection

OpenDPR: Open-Vocabulary Change Detection via Vision-Centric Diffusion-Guided Prototype Retrieval for Remote Sensing Imagery

A toolkit that enables building damage assessments from remotely sensed imagery.

High Speed Assessment and Satellite Tracking for Emergencies

Citation Extraction & Reference Checking Assistant

[CVPR 2026 Oral] "INSID3: Training-Free In-Context Segmentation with DINOv3"

Run neural networks via GDAL CLI

Official Implementation of Upsample Anything: A Simple and Hard to Beat Baseline for Feature Upsampling

Code for GEO-Bench V2 datasets. Made in collaboration with TUM, IBM and ServiceNow.

Implementation of a binary change detection system for EO-SAR image pairs using U-Net with ResNet34 backbone, PyTorch, and multimodal satellite imagery segmentation.

Remote Sensing Change Net is a PyTorch-based change detection project for remote sensing imagery, using a Siamese transformer architecture to detect pixel-level changes between bi-temporal satellit…

Code Repo for Earth Observation for Disaster Mapping: Benchmarks, Methods, Challenges and Future Perspectives

[IEEE TGRS 2024] Learning Land-Cover Changes from Satellite and Map Data via Object-Guided Transformer

[CVPR 2026] UniChange: Unifying Change Detection with Multimodal Large Language Model

[CVPR 2025] Official Implementation of "Dinomaly: The Less Is More Philosophy in Multi-Class Unsupervised Anomaly Detection". The first multi-class UAD model that can compete with single-class SOTAs

Official repo for the paper "No One Knows the State-of-the-Art in Geospatial Foundation Models"

[CVPR 2026 Oral] VGGT Omega