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Our research introduces the MS-Diffusion framework for layout-guided zero-shot image personalization with multi-subjects. This innovative approach integrates grounding tokens with the feature resampler to maintain detail fidelity among subjects. With the layout guidance, MS-Diffusion further improves the cross-attention to adapt to the multi-subject inputs, ensuring that each subject condition acts on specific areas. The proposed multi-subject cross-attention orchestrates harmonious inter-subject compositions while preserving the control of texts.
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- **GitHub:** [https://github.com/Maitreyapatel/lambda-eclipse-inference](https://github.com/Maitreyapatel/lambda-eclipse-inference)
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Our research introduces the MS-Diffusion framework for layout-guided zero-shot image personalization with multi-subjects. This innovative approach integrates grounding tokens with the feature resampler to maintain detail fidelity among subjects. With the layout guidance, MS-Diffusion further improves the cross-attention to adapt to the multi-subject inputs, ensuring that each subject condition acts on specific areas. The proposed multi-subject cross-attention orchestrates harmonious inter-subject compositions while preserving the control of texts.
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- **Project Page:** [https://eclipse-t2i.github.io/Lambda-ECLIPSE/](https://eclipse-t2i.github.io/Lambda-ECLIPSE/)
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- **GitHub:** [https://github.com/Maitreyapatel/lambda-eclipse-inference](https://github.com/Maitreyapatel/lambda-eclipse-inference)
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