license: apache-2.0
SFM: Spatial Frequency Modulation for Semantic Segmentation (TPAMI 2025)
Official checkpoints for the paper Spatial Frequency Modulation for Semantic Segmentation (TPAMI 2025, arXiv:2507.11893, DOI 10.1109/TPAMI.2025.3592621).
Code: https://github.com/Linwei-Chen/SFM
Two released technical lines:
- Line 1 — FCN-style models: ARS + qhull non-uniform upsampling (MSAU, paper Eq. 17/18)
- cascaded LPRM, built on mmsegmentation 0.25.0.
Eval code and the 18 configs:
SFM_mmseg0x/.
- cascaded LPRM, built on mmsegmentation 0.25.0.
Eval code and the 18 configs:
- Line 2 — FPN: ARS + CARAFE-style feature reassembly with 3-point dynamic-sampling
weighted alignment, on Mask2Former (mmsegmentation 1.x).
Code and config:
SFM_mask2former/.
Every checkpoint below is verified from training/eval logs: each measured mIoU either
exceeds the paper-reported number or matches it after one-decimal rounding
(e.g. PSPNet-R50 D16 measures 78.05, rounding to the paper's 78.1). Each model folder
contains config.py (the exact config paired with that checkpoint) and the weight file.
Line 1 — Cityscapes (val mIoU, ResNet-50)
| folder | paper | measured |
|---|---|---|
line1/cityscapes/ccnet_r50SS3PR-d32_cityscapes |
76.3 | 76.34 |
line1/cityscapes/ccnet_r50SS3PR-d16_cityscapes |
78.5 | 78.45 |
line1/cityscapes/ccnet_r50SS3PR-d8_cityscapes |
79.3 | 79.39 |
line1/cityscapes/isanet_r50SS3PR-d32_cityscapes (OCNet) |
75.8 | 75.82 |
line1/cityscapes/isanet_r50SS3PR-d16_cityscapes (OCNet) |
78.0 | 78.00 |
line1/cityscapes/isanet_r50SS3PR-d8_cityscapes (OCNet) |
79.7 | 79.74 |
line1/cityscapes/FCN_r50SS3PR-d32_cityscapes |
76.2 | 76.20 |
line1/cityscapes/FCN_r50SS3PR-d16_cityscapes |
77.8 | 77.78 |
line1/cityscapes/FCN_r50SS3PR-d8_cityscapes |
78.7 | 78.65 |
line1/cityscapes/pspnet_r50SS3PR-d32_cityscapes |
76.0 | 76.18 |
line1/cityscapes/pspnet_r50SS3PR-d16_cityscapes |
78.1 | 78.05 |
line1/cityscapes/pspnet_r50SS3PR-d8_cityscapes |
79.5 | 79.52 |
line1/cityscapes/pcaa_r50SSPR-d32_cityscapes (PCAA, col. 1) |
76.8 | 76.83 |
line1/cityscapes/pcaa_r50SSPR-d16_cityscapes (PCAA, col. 2) |
77.9 | 77.86 |
Weight file in each folder: iter_40000.pth.
Line 1 — PascalContext-59 (val mIoU, ResNet-50)
| folder | paper | measured |
|---|---|---|
line1/pascalcontext/FCN_r50SS3PR-d32_pascalcontext |
46.0 | 46.35 |
line1/pascalcontext/pspnet_r50SS3PR-d32_pascalcontext |
49.7 | 49.68 |
line1/pascalcontext/ccnet_r50SS3PR-d32_pascalcontext |
49.1 | 49.07 |
line1/pascalcontext/isanet_r50SS3PR-d32_pascalcontext (OCNet) |
49.9 | 49.85 |
Line 2 — ADE20K (val mIoU, Mask2Former Swin-T)
| folder | paper | measured |
|---|---|---|
line2/mask2former_swin-t_8xb2-160k_ade20k-512x512_SFMv2 |
49.1 | 49.34 (re-evaluated 2025-10) |
Weight file: best_mIoU_iter_150000.pth.
Evaluation
Line 1 (see SFM_mmseg0x/README.md
for environment setup and qhull compilation):
cd SFM_mmseg0x # from the GitHub repo checkout
PYTHONPATH=<SFM_mmseg0x> python tools/test.py \
<model_folder>/config.py <model_folder>/iter_40000.pth --eval mIoU
Line 2 (code: SFM_mask2former/,
mmsegmentation 1.x):
cd SFM_mask2former
python tools/test.py \
<model_folder>/config.py <model_folder>/best_mIoU_iter_150000.pth
Citation
@article{chen2023spatialfrequency,
title={Spatial Frequency Modulation for Semantic Segmentation},
author={Chen, Linwei and Fu, Ying and Gu, Lin and Zheng, Dezhi and Dai, Jifeng},
journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
year={2025},
volume={47},
number={11},
pages={9767-9784},
doi={10.1109/TPAMI.2025.3592621}
}
Code is released under the Apache-2.0 license.