✨EVTAR: End-to-End Try on with Additional Unpaired Visual Reference

📝 Summary:
EVTAR is an end-to-end virtual try-on model that enhances accuracy and garment detail preservation using additional reference images. It simplifies the process by requiring only source and target garment inputs, producing high-quality, realistic try-on results.

🔹 Publication Date: Published on Nov 2

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.00956
• PDF: https://arxiv.org/pdf/2511.00956
• Github: https://github.com/360CVGroup/EVTAR

🔹 Models citing this paper:
• https://huggingface.co/qihoo360/EVTAR

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✓ https://t.iss.one/DataScienceT

#VirtualTryOn #ComputerVision #DeepLearning #AIFashion #ImageSynthesis

✨MMaDA-Parallel: Multimodal Large Diffusion Language Models for Thinking-Aware Editing and Generation

📝 Summary:
A parallel multimodal diffusion framework, MMaDA-Parallel, enhances cross-modal alignment and semantic consistency in thinking-aware image synthesis by addressing error propagation issues in sequentia...

🔹 Publication Date: Published on Nov 12

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.09611
• PDF: https://arxiv.org/pdf/2511.09611
• Project Page: https://tyfeld.github.io/mmadaparellel.github.io/
• Github: https://github.com/tyfeld/MMaDA-Parallel

🔹 Models citing this paper:
• https://huggingface.co/tyfeld/MMaDA-Parallel-A
• https://huggingface.co/tyfeld/MMaDA-Parallel-M

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For more data science resources:
✓ https://t.iss.one/DataScienceT

#MultimodalAI #DiffusionModels #ImageSynthesis #LLM #AIResearch