Peking University Introduces UniWorld-Design for Layer-Native Image Generation
PekingUniversity · hf · 2026-08-05
Peking University introduced UniWorld-Design, a framework that redefines image generation from flat pixel synthesis to structured visual composition, using semantic RGBA layers as atomic units for generation, understanding, and editing.
Core Models
- Text-to-RGBA (T2RGBA): Generates standalone RGBA assets directly from text.
- Image-to-Layer (I2L): Conditions on a finished image, global instructions, and per-layer prompts to jointly produce ordered, complete semantic RGBA layers. Because it learns complete semantic objects rather than visible-pixel partitions, its layers remain usable when moved or removed.
Performance
- On the Crello benchmark, I2L reduces per-layer RGB L1 error by 37% and achieves a 34% relative improvement in Alpha Soft IoU over Qwen-Image-Layered.
- T2RGBA achieves the highest CLIP Score, outperforming LayerDiffuse and OmniAlpha.
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