qihoo360/RevealLayer

Disentangling Hidden and Visible Layers via Occlusion-Aware Image Decomposition

Binhao Wang^1,2,*, Shihao Zhao^1,2,*, Bo Cheng^2,*,†, Qiuyu Ji^1,2, Yuhang Ma²,
Liebucha Wu², Shanyuan Liu², Dawei Leng^2,‡, Yuhui Yin²

¹Wenzhou University ²360 AI Research

^* Equal Contribution. ^† Project Lead. ^‡ Corresponding Author.

🔥 Accepted by ICML 2026!

     

RevealLayer decomposes an RGB image into multiple RGBA layers, enabling precise layer separation and reliable recovery of occluded content in natural scenes.

For more visual results, go checkout our project page.

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⭐ Update

• [2026.05] RevealLayer has been accepted by ICML 2026.
• [2026.05] We released the RevealLayer paper and inference code.
• [2026.05] We released the RevealLayer checkpoint on Hugging Face.

✅ TODO

• Release RevealLayer-100K and RevealLayerBench.
• Release an improved version of RevealLayer with stronger layer consistency and higher inference efficiency.

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🎃 Overview

RevealLayer focuses on occlusion-aware image layer decomposition, recovering visible and hidden RGBA layers from a single RGB image with region guidance.

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📷 Datasets

We construct a large-scale multi-layer image decomposition dataset, including RevealLayer-100K for training and RevealLayerBench for evaluation. RevealLayer-100K contains 100K multi-layer natural image tuples with RGB images, background layers, RGBA foreground layers, and bounding boxes. RevealLayerBench contains 200 high-quality manually curated images, covering challenging cases such as complex occlusions, large-area objects, transparent materials, small foreground objects, and multi-layer scenes.

🔥 We will release RevealLayer-100K and RevealLayerBench on Hugging Face. We hope they can serve as useful training and evaluation resources for future research on occlusion-aware image layer decomposition.

🚩 The datasets are intended for research use. Please follow the license and terms provided with the released dataset.

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📑 Citation

If you find our work useful for your research, please consider citing:

@inproceedings{wang2026reveallayer,
  title={RevealLayer: Disentangling Hidden and Visible Layers via Occlusion-Aware Image Decomposition},
  author={Wang, Binhao and Zhao, Shihao and Cheng, Bo and Ji, Qiuyu and Ma, Yuhang and Wu, Liebucha and Liu, Shanyuan and Leng, Dawei and Yin, Yuhui},
  booktitle={International Conference on Machine Learning},
  year={2026}
}

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📝 License

This project is licensed under the Apache License 2.0.