Datasets and trained diffusion models for "Diffusion Models for Interferometric Satellite Aperture Radar"
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下载链接：
https://zenodo.org/record/8222778
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资源简介：
A set of trained Probabilistic Diffusion Models (PDMs) and corresponding training datasets for the paper "Diffusion Models for Interferometric Satellite Aperture Radar", by Tuel, Kerdreux et al. The code for this paper can be found at this link.
Training datasets
- "InSAR_noise_32x32.zip": a dataset of 32x32 ground deformation scenes obtained from InSAR interferograms over New Mexico with the small baseline subset (SBAS) algorithm. Images were normalised to [0, 1].
- "insar_unwrapped_phase_normalised.zip": a dataset of 128x128 InSAR interferograms obtained from Sentinel-1 acquisitions over Nex Mexico. Images were normalised to [0, 1].
Trained Models
We provide 6 trained PDMs in separate .zip files. Each .zip file contains the model weights (in *.pt format) and the model metadata file (in *.json format).
- "mnist_32_cond_sigma_100.zip": a class-conditional model trained with 100 diffusion time steps on 32x32 MNIST images;
- "mnist_32_no_cond_sigma_100.zip": an unconditional model trained with 100 diffusion time steps on 32x32 MNIST images;
- "SAR_lowres_128_cond_sigma_2000.zip": a low-resolution (256 to 128) model trained with 2000 diffusion time steps on 128x128 TenGeoP-SARwv images;
- "SAR_superres_128_to_256_cond_sigma_2000.zip": a super-resolution (128 to 256) model trained with 2000 diffusion time steps on TenGeoP-SARwv images;
- "insar_phase_128_sigma_2000.zip": an unconditional model trained with 2000 diffusion time steps on 128x128 Sentinel-1 InSAR interferograms over New Mexico;
- "insar_noise_32_sigma_1000.zip": an unconditional model trained with 1000 diffusion time steps on 32x32 Sentinel-1 InSAR ground deformation scenes over New Mexico.
创建时间：
2023-09-02
