Naughtyba

SSL4EO_base

model

The Clay Foundation Model (in development)

Paraformer

Paraformer: Updating Large-scale High-resolution Land Cover Maps from Low-resolution Historical Labels

EfficientBigEarthNet

Code and models for efficient training on the BigEarthNet dataset for Land Use Land Cover classification

DiffusionSat

Official code repository for ICLR 2024 paper "DiffusionSat: A Generative Foundation Model for Satellite Imagery"

HighResCanopyHeight

This repository provides inference code to compute canopy height maps from aerial images, as described in the paper "Very high resolution canopy height maps from RGB imagery using self-supervised vision transformer and convolutional decoder trained on Aerial Lidar".

asip-v1

Code for ASIP project publication, Dec. 2019.

Depth-Anything

[CVPR 2024] Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data. Foundation Model for Monocular Depth Estimation

MMIF-DDFM

[ICCV 2023 Oral] Official implementation for "DDFM: Denoising Diffusion Model for Multi-Modality Image Fusion."

global-canopy-height-model

This repository contains the code used in the paper: A high-resolution canopy height model of the Earth. Here, we developed a model to estimate canopy top height anywhere on Earth. The model estimates canopy top height for every Sentinel-2 image pixel and was trained using sparse GEDI LIDAR data as a reference.

pytorch-image-classification

Tutorials on how to implement a few key architectures for image classification using PyTorch and TorchVision.