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LOCATION:Room 408 B
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UID:siggraph_SIGGRAPH 2026_sess156_papers_760@linklings.com
SUMMARY:MV-S2V: Multi-View Subject-Consistent Video Generation
DESCRIPTION:Ziyang Song (The Hong Kong Polytechnic University), Xinyu Gong
  (The University of Texas at Austin), Bangya Liu (University of Wisconsin-
 Madison), and Zelin Zhao (Georgia Institute of Technology)\n\nMV-S2V is th
 e first work to explore video generation with multi-view subject consisten
 cy. It presents a simple yet effective framework, including a tailored dat
 a curation pipeline and a Temporally-Shifted RoPE (TS-RoPE) specially desi
 gned for multi-view reference conditioning, achieving superior 3D subject 
 consistency w.r.t. multi-view reference images and high-quality visual out
 puts.\n\nInterest Area: Research & Education\n\nKeyword: Artificial Intell
 igence/Machine Learning, Generative AI, Rendering\n\nRegistration Category
 : Full Conference Supporter, Full Conference\n\nSession Chair: Ayush Tewar
 i (Cambridge University)\n\n
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