DIRS Models and Data

This repository hosts the released checkpoints and TJReflection real-world data for DIRS: Principled Reflection Separation via Nonlinear Superposition and Feature Interaction.

DIRS studies reflection separation under a nonlinear sRGB image formation model and provides three released variants:

  • DIRS-YTMT: CNN interaction through feature recycling.
  • DIRS-MuGI: CNN interaction through mutual gating.
  • DIRS-PAIR: Transformer-based dual-stream joint attention.

Repository Contents

checkpoints/
  dirs_ytmt_lors.ckpt
  dirs_mugi_lors.ckpt
  dirs_pair_lors.ckpt
  dirs_pair_lors_nature.ckpt
  rsr_supplement.ckpt
  polarized_dirs_pair_lors.ckpt
  pretrained/
    swin_large_o365.pth
datasets/
  TJReflection/

datasets/TJReflection/ contains 175 real-world reflection images used by the DIRS release.

Checkpoints

Metrics are reported on the LORS test setting at 256 x 256 resolution. Runtime is measured on a single NVIDIA RTX 3090.

Model Type Params FLOPs Time PSNR SSIM File
DIRS-YTMT CNN, activation interaction 32.42M 102.91G 31.35 ms 24.94 0.902 checkpoints/dirs_ytmt_lors.ckpt
DIRS-MuGI CNN, mutual gating 84.47M 153.98G 49.95 ms 25.63 0.913 checkpoints/dirs_mugi_lors.ckpt
DIRS-PAIR Transformer, joint attention 48.80M 200.22G 75.36 ms 26.37 0.918 checkpoints/dirs_pair_lors.ckpt
DIRS-PAIR + Nature Transformer, joint attention 48.80M 200.22G 75.36 ms 26.95 0.926 checkpoints/dirs_pair_lors_nature.ckpt

Supplementary checkpoints:

Task File Notes
Reflection scene reconstruction checkpoints/rsr_supplement.ckpt Supplementary model for reconstructing reflection scenes.
Polarized reflection separation checkpoints/polarized_dirs_pair_lors.ckpt DIRS-PAIR adapted to polarized inputs.
Swin prior checkpoints/pretrained/swin_large_o365.pth Pretrained prior used by DIRS-PAIR and polarized DIRS.

Usage

Clone this repository or download it from the Hugging Face UI, then place checkpoints/ and datasets/ at the root of the DIRS code repository:

git clone https://github.com/mingcv/DIRS.git
cd DIRS
git clone https://huggingface.co/huqiming513/DIRS-Models DIRS-Models
cp -r DIRS-Models/checkpoints .
cp -r DIRS-Models/datasets .

Example evaluation command:

python -m xreflection.test \
  --config options/test_dirs_pair_lors.yml \
  --resume checkpoints/dirs_pair_lors.ckpt

Available evaluation configs in the code repository:

Model Config Checkpoint
DIRS-YTMT options/test_dirs_ytmt_lors.yml checkpoints/dirs_ytmt_lors.ckpt
DIRS-MuGI options/test_dirs_mugi_lors.yml checkpoints/dirs_mugi_lors.ckpt
DIRS-PAIR options/test_dirs_pair_lors.yml checkpoints/dirs_pair_lors.ckpt
DIRS-PAIR + Nature options/test_dirs_pair_lors.yml checkpoints/dirs_pair_lors_nature.ckpt

Intended Use

These files are intended for academic research and reproducibility in image reflection separation, reflection scene reconstruction, and polarized reflection separation. The models are not designed as a safety-critical restoration system and may fail on images outside the training and evaluation distribution, including unusual glass materials, severe saturation, extreme low light, or strong misalignment.

Citation

If you use these checkpoints, data, or code, please cite:

@article{hu2026dirs,
  title={Principled Reflection Separation via Nonlinear Superposition and Feature Interaction},
  author={Hu, Qiming and Li, Mingjia and Li, Yuntong and Guo, Xiaojie},
  journal={arXiv preprint},
  year={2026}
}
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