✨DreamID-V:Bridging the Image-to-Video Gap for High-Fidelity Face Swapping via Diffusion Transformer

📝 Summary:
DreamID-V is a novel video face swapping framework that uses diffusion transformers and curriculum learning. It achieves superior identity preservation and visual realism by bridging the image-to-video gap, outperforming existing methods and enhancing temporal consistency.

🔹 Publication Date: Published on Jan 4

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.01425
• PDF: https://arxiv.org/pdf/2601.01425
• Project Page: https://guoxu1233.github.io/DreamID-V/
• Github: https://guoxu1233.github.io/DreamID-V/

==================================

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

#FaceSwapping #DiffusionModels #ComputerVision #GenerativeAI #VideoAI