Ymx1025/DamageTriageFormer-model

Damage-TriageFormer (trained checkpoint)

Trained weights for Damage-TriageFormer, a foundation-model framework for decision-relevant building damage typology from single post-event imagery. Given a post-event RGB tile and building instance masks (footprints), the model assigns each building one of five damage-typology classes:

Class	Name
0	Undamaged
1	Partial Roof Damage
2	Total Roof Damage
3	Partial Structural Damage
4	Total Structural Collapse

Files

• best_model.pth — the reported checkpoint, selected by validation macro-F1 in the footprint-conditioned setting.
• config.json — the exact training configuration used to produce it.

Architecture

DINOv3 ViT-L/16 backbone (last 4 blocks fine-tuned) → Simple Feature Pyramid (target stride 8, 128×128 feature map) → mask-pooled instance features → a two-stage gated damage head (any-damage gate → 4-way damaged-class leaf), with an auxiliary severity-regression head used during training.

Training

30 epochs, AdamW (LR 5e-5 heads / 5e-6 backbone), effective batch 32 (2×A100 40GB, DDP), label smoothing 0.1, EMA (decay 0.9995), long-tailed logit adjustment (τ=1.0), inverse-square-root class weighting on the leaf head. Trained on DamageTriage-Bench (Hurricane Michael 2018, Hurricane Helene 2024, and the 2025 Los Angeles wildfire complex).

Results

Macro F1 0.624 (validation) / 0.619 (held-out test) on the stratified split; per-class test F1 of 0.91 (Undamaged) and 0.84 (Total Structural Collapse). Total Roof Damage remains the hardest class (F1 ≈ 0.33).

Usage

Load these weights with the training/inference code: github.com/YimingXiao98/Damage-TriageFormer (MIT). The model expects a 1024×1024 post-event RGB tile and building instance masks, and returns a 5-class damage-typology probability per building.

Training data

DamageTriage-Bench: huggingface.co/datasets/Ymx1025/DamageTriage-Bench (CC-BY-NC-4.0).

Intended use and limitations

Screening-grade decision support for post-disaster triage, not a substitute for engineering inspection. Footprint-conditioned (assumes building masks are available). Rare and visually ambiguous roof-damage categories, especially Total Roof Damage, are the least reliable. Trained on a single seed.

License

Released under CC-BY-NC-4.0, consistent with the DamageTriage-Bench dataset it was trained on. Subject to the redistribution terms of the underlying NOAA Emergency Response Imagery and the source building-footprint layers.

Citation

@misc{xiao2026damagetriageformerfoundationmodelframeworktypologybased,
      title={Damage-TriageFormer: A Foundation-Model Framework for Typology-Based Building Damage Assessment from Mono-Temporal Imagery}, 
      author={Yiming Xiao and Yu-Hsuan Ho and Sanjay Thasma and Junwei Ma and Ali Mostafavi},
      year={2026},
      eprint={2606.12248},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2606.12248}, 
}