tangkai-RS/DreamCD
[JAG 2026] DreamCD: A change-label-free framework for change detection via a weakly conditional semantic diffusion model in optical VHR imagery
This project helps environmental analysts, urban planners, and disaster responders identify changes in very high-resolution satellite imagery over time, without needing pre-labeled examples of what 'change' looks like. You provide two satellite images of the same area taken at different times, and it outputs a new 'post-event' image that highlights the detected changes, along with a mask clearly showing where changes occurred. This is useful for anyone monitoring land use, deforestation, or damage after natural disasters.
Use this if you need to detect changes in satellite or aerial imagery but lack extensive, manually labeled datasets of 'changed' and 'unchanged' areas.
Not ideal if you require real-time change detection for streaming data or if you primarily work with lower-resolution imagery.
Stars
22
Forks
1
Language
Python
License
—
Category
Last pushed
Jan 30, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/diffusion/tangkai-RS/DreamCD"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
cswry/SeeSR
[CVPR2024] SeeSR: Towards Semantics-Aware Real-World Image Super-Resolution
JJLibra/SALAD-Pan
🤗 Official implementation for "SALAD-Pan: Sensor-Agnostic Latent Adaptive Diffusion for...
open-mmlab/mmgeneration
MMGeneration is a powerful toolkit for generative models, based on PyTorch and MMCV.
Janspiry/Image-Super-Resolution-via-Iterative-Refinement
Unofficial implementation of Image Super-Resolution via Iterative Refinement by Pytorch
hanjq17/Spectrum
[CVPR 2026] Adaptive Spectral Feature Forecasting for Diffusion Sampling Acceleration