Zhu X Lab

weights

open(ungated CC-BY-4.0 DOFA and DOFA v2 checkpoints on Hugging Face)

data

documented-not-released(paper section 6 gives the composition — ~11.5M images across Sentinel-1, Sentinel-2, NAIP, Gaofen and EnMAP, with per-modality channel counts — and a download link per subset, but no assembled DOFA corpus and no script that rebuilds it end to end)

code

open(pretraining entry point, masked-autoencoder engine, samplers, and launch script under pretraining/)

license

CC-BY-4.0(attribution only, not OSI-approved)

The pretraining pipeline is public, the checkpoints are ungated, and the paper documents the corpus well enough to audit the mixture: section 6 Data availability statements names all five subsets with a download link each. That pairs a described corpus with an open pipeline, which is the rung the ladder writes for exactly this case. It is recorded as documented-not-released rather than open because the constituents are third-party datasets and nothing assembles them — no DOFA corpus is published and no script rebuilds one. The score is 4 on either reading. The repository LICENSE is MIT and covers the code; the weights the Hub distributes are CC-BY-4.0, and that is the license this axis scores.

• https://huggingface.co/api/models/earthflow/DOFA recorded 2026-09-10

  gated: false; private: false; license cc-by-4.0; DOFA_ViT_base_e100.pth, DOFA_ViT_large_e100.pth, dofav2_vit_base_e150.pth, and dofav2_vit_large_e150.pth present.

• https://huggingface.co/earthflow/DOFA/raw/main/README.md recorded 2026-09-10

  Card front matter and the model details both state License: CC-BY-4.0 for the released DOFA weights.

• https://api.github.com/repos/zhu-xlab/DOFA/contents/pretraining recorded 2026-09-10

  Lists main_pretrain_ofa.py, engine_pretrain.py, models_base_ofa_mae.py, train_mae_all.sh, samplers, and a datasets directory holding only a loader and wavelength tables.

• https://arxiv.org/abs/2403.15356 recorded 2026-09-10

  Abstract states that the code and pretrained weights are publicly available. It says nothing either way about the corpus, so it establishes the artifacts and not the data dimension.

• https://arxiv.org/pdf/2403.15356v3 recorded 2026-09-10

  Section 4.5 — "DOFA is pretrained on a large-scale multimodal EO dataset comprising approximately 11.5 million images from five different modalities: Sentinel-1, Sentinel-2, NAIP, Gaofen, and EnMAP". Section 6 Data availability statements gives a download link per subset (SatlasPretrain for Sentinel-1 and Sentinel-2, a named Drive folder for Gaofen, hyspecnet.rsim.berlin for EnMAP).