Downloads · 30 days
0
Alvaritox/seasonstereo
seasonstereo is a machine learning model from Alvaritox. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
Final SeasonStereo weights: MonSter++ fine-tuned for diachronic stereo matching on multi-date satellite imagery (pseudo-GT disparity + photometric + edge-aware smoothness losses).
Downloads · 30 days
0
Access
Public
Updated Sep 2, 2026
Repo size
1.6 GB
Likes
0
Public
Click a slice to open those files.
.pth1.6 GB · 100%
From the Hugging Face model README
Final SeasonStereo weights: MonSter++ fine-tuned for diachronic stereo matching on multi-date satellite imagery (pseudo-GT disparity + photometric + edge-aware smoothness losses).
hf download Alvaritox/seasonstereo season-stereo-final.pth --local-dir checkpoints
bash season_stereo/run_evaluation.sh
The checkpoint is loaded by the training/evaluation code in the GitHub repository; see its
README.md for environment setup and the expected data/ layout.
Average altitude MAE of 1.05 m on the diachronic test set, matching the LiDAR-supervised variant.
@inproceedings{diaz-laureano2026seasonstereo,
title = {SeasonStereo: Robust Dense Stereo Matching for Multi-Date Satellite Imagery via Generative AI},
author = {D{\'\i}az-Laureano, {\'A}lvaro and Mar{\'\i}, Roger and Masquil, El{\'\i}as and Arias, Pablo and Facciolo, Gabriele},
booktitle = {Proceedings of the TerraBytes II Workshop at the European Conference on Computer Vision (ECCV)},
year = {2026}
}