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lino-lvc-checkpoints

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photometric-stereo
normal-estimation
lino-unips
lvc
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metadata 
license: mit
tags:
  - photometric-stereo
  - normal-estimation
  - lino-unips
  - lvc
library_name: pytorch

LiNo-UniPS + LVC checkpoints

Checkpoints for bachelor thesis: Lighting Variation Confidence (LVC) module on LiNo-UniPS — Đoàn Anh Vũ, HUST SOICT.

Variants

Folder Variant Description
bl_real_* baseline Original LiNo-UniPS (no LVC)
fl_real_* lvc_full LiNo-UniPS + LVC full (loss weighting + feature scaling, proposed method)
ll_real_* lvc_loss LVC loss weighting only (ablation)
lf_real_* lvc_feat LVC feature scaling only (ablation)

Filename convention: {variant_short}_{mode}_{DDMMYYYY}_{HHMMSS}_e{epoch}_v{val_loss}.ckpt

  • variant_short: bl / fl / ll / lf
  • mode: smoke (test) / real (production)

Training setup

  • Dataset: HDLong + (PolarPS future), hosted at HUST-CVLab-PS/UniPS
  • Hardware: NVIDIA RTX 6000 Ada (Vast.ai)
  • Optimizer: AdamW(lr=1e-4, wd=0.05), StepLR(step=10, gamma=0.8)
  • Precision: bf16-mixed
  • K input images: 6 (HDLong)
  • Hyperparams khác xem wandb run config

Acknowledgments

Base architecture & weights: LiNo-UniPS (MIT License) by H. Li, H. Chen et al.

License

MIT — same as upstream LiNo-UniPS.