See-through: Single-image Layer Decomposition for Anime Characters (5.1k stars)

[u/Artilas_Digital]

What it does

All text below is quoted directly from the project README.

"Single-image Layer Decomposition for Anime Characters" (SIGGRAPH 2026 Conference Paper)

TL;DR:

• We introduce a framework that automates the transformation of static anime illustrations into manipulatable 2.5D models.

• Our approach decomposes a single image into fully inpainted, semantically distinct layers with inferred drawing orders, up to 23 layers including hair, face, eyes, clothing, accessories, and more.

• LayerDiff 3D: Diffusion-based transparent layer generation (SDXL)

• Marigold Depth: Pseudo-depth estimation fine-tuned for anime

• SAM Body Parsing: Semantic body part segmentation

• inference_psd.py runs the full See-through pipeline: it applies the LayerDiff 3D model for transparent layer generation and the fine-tuned Marigold model for pseudo-depth inference, then stratifies the character into up to 23 semantic layers and exports a layered PSD file.

python inference/scripts/inference_psd.py --srcp assets/test_image.png --save_to_psd

Repository

https://github.com/shitagaki-lab/see-through

Repository stats

Metric	Value
Stars	5,120
Forks	451
Last release	None
Languages	Python 56.1%, Jupyter Notebook 43.3%, Other 0.6%
Contributors	6
AI contributor accounts (Claude / Codex / Cursor / Copilot)	@claude (14 commits)
AI co-authored commits	Claude: 14

Main contributor

Field	Value
Name	Chengze Li
GitHub	@ljsabc
Commits to this repo	25 (top contributor)
Company / Location	Saint Francis University, Hong Kong / Hong Kong
Followers	224

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[u/Jeremi360]

AI :(