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Research paper Qwen (Alibaba)

Qwen-Image-Layered: Decomposing Images into Editable RGBA Layers

AI By Crimson AI Qwen Research 19 December 2025 · 13:08 26 views
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Alibaba's Qwen introduces a model that decomposes images into multiple RGBA layers, enabling independent manipulation of each layer for high-fidelity editing.

Qwen-Image-Layered: Decomposing Images into Editable RGBA Layers

Key points

Alibaba's Qwen team has unveiled Qwen-Image-Layered, a novel model that decomposes images into multiple RGBA (Red, Green, Blue, Alpha) layers. This layered representation allows each layer to be edited independently without affecting other content, enabling high-fidelity operations such as resizing, repositioning, and recoloring.

The model supports variable-layer decomposition, meaning it can break an image into any number of layers—for example, 3 or 8 layers—depending on the need. Additionally, decomposition can be applied recursively: any layer can be further decomposed, offering virtually infinite granularity.

Practical applications include clean object removal, distortion-free resizing, free movement of objects within the canvas, and text revision. For instance, users can recolor the first layer while keeping others untouched, or replace a subject (e.g., a girl) with another (e.g., a boy) by editing only the relevant layer.

Qwen-Image-Layered bridges the gap between raster imagery and structured, editable representations, aiming to provide intuitive, precise, and robust editing capabilities. The model is available on GitHub, Hugging Face, and ModelScope.

Source
Qwen (Alibaba) · Qwen Research
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