latentvector1/safe-checkpoints

SAFe — trained conditional normalizing-flow checkpoints

Anonymous checkpoint release accompanying a paper submission under double-blind review. This repository hosts the trained normalizing-flow weights; all code, configs, and instructions are in the anonymized code repository linked from the paper.

Contents

checkpoints/
  flows/                                  # trained conditional normalizing flows
    convnext_l_res4_cityscapes/checkpoint_best.ckpt
    convnext_l_res4_issu/checkpoint_best.ckpt
    convnext_l_res5_cityscapes/checkpoint_best.ckpt
    convnext_l_res5_issu/checkpoint_best.ckpt
    vit_l_res5_cityscapes/checkpoint_best.ckpt
    vit_l_res5_issu/checkpoint_best.ckpt
  priors/                                 # per-class Gaussian priors
    convnext_l_res4_cityscapes.pth
    convnext_l_res4_issu.pth
    convnext_l_res5_cityscapes.pth
    convnext_l_res5_issu.pth
    vit_l_cityscapes.pth
    vit_l_issu.pth

Checkpoint	Backbone	Feature level	Training data
convnext_l_res4_cityscapes	DINOv3 ConvNeXt-L	res4	Cityscapes (train)
convnext_l_res5_cityscapes	DINOv3 ConvNeXt-L	res5	Cityscapes (train)
vit_l_res5_cityscapes	DINOv3 ViT-L	last block	Cityscapes (train)
convnext_l_res4_issu	DINOv3 ConvNeXt-L	res4	ISSU-static (train)
convnext_l_res5_issu	DINOv3 ConvNeXt-L	res5	ISSU-static (train)
vit_l_res5_issu	DINOv3 ViT-L	last block	ISSU-static (train)

Usage

Clone the anonymized code repository, then download this repo's checkpoints/ directory to the repo root:

from huggingface_hub import snapshot_download

snapshot_download(
    repo_id="<ANON-USER>/safe-checkpoints",
    repo_type="model",
    local_dir=".",
    allow_patterns=["checkpoints/**"],
)

License

Released for the purpose of peer review and research reproducibility only.