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[ICASSP 2026] Beyond Shadows: A Large-Scale Benchmark and Multi-Stage Framework for High-Fidelity Facial Shadow Removal

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Beyond Shadows: A Large-Scale Benchmark for High-Fidelity Facial Shadow Removal

Tailong Luo , Yihang Dong , Jiesong Bai , Junyu Xia , Jinyang Huang , Wangyu Wu , Xuhang Chen 📮 (📮 Corresponding author)

New York Institute of Technology, SIAT CAS, Shanghai University, Central South University, Xi'an Jiaotong-Liverpool University, Huizhou Univeristy

In IEEE International Conference on Acoustics, Speech, and Signal Processing 2026 (ICASSP 2026)

🔮 Dataset

The benchmark datasets are available at Kaggle.

⚙️ Usage

Training

You may download the dataset first, and then specify TRAIN_DIR, VAL_DIR and SAVE_DIR in the section TRAINING in config.yml.

For single GPU training:

python train.py

For multiple GPUs training:

accelerate config
accelerate launch train.py

If you have difficulties with the usage of accelerate, please refer to Accelerate.

Inference

Please first specify TRAIN_DIR, VAL_DIR and SAVE_DIR in section TESTING in config.yml.

python test.py

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