Omni-R2V is now on ModelScope! 339,570 training samples for teaching video models to follow image and video references beyond a single subject.
🤖 https://modelscope.ai/datasets/TencentOVBU/OmniR2V
📄 https://modelscope.ai/papers/2609.22069

🧩 Seven reference controls: Content, motion, style, structure, narrative, multi-content, and cross-aspect.
🎬 Flexible multi-reference training: Each sample includes candidate references, bilingual instructions defining their roles, and a target video. Train with one reference, matched pairs, or compatible subsets.
🔊 Audio when available: Retained target audio also supports reference-to-audiovisual research.
📊 Train and evaluate the same controls: OmniVBench adds 813 cases, 18 tasks, and 12,172 checklist items for reference fidelity and instruction following.
📜 Research use only. Commercial use and media redistribution are not covered.