Introducing our new work: OpenS2V-Nexus: A Detailed Benchmark and Million-Scale Dataset for Subject-to-Video Generation​​ 🚀
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Introducing our new work: OpenS2V-Nexus: A Detailed Benchmark and Million-Scale Dataset for Subject-to-Video Generation​​ 🚀
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We tackle the core challenges of ​​Subject-to-Video Generation (S2V)​​ by systematically building the first complete infrastructure—featuring an evaluation benchmark and a million-scale dataset! ✨
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We tackle the core challenges of ​​Subject-to-Video Generation (S2V)​​ by systematically building the first complete infrastructure—featuring an evaluation benchmark and a million-scale dataset! ✨
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🧠 Introducing ​​OpenS2V-Eval​​—the first ​​fine-grained S2V benchmark​​, with ​​180 multi-domain prompts + real/synthetic test pairs​​. We propose ​​NexusScore​​, ​​NaturalScore​​, and ​​GmeScore​​ to precisely quantify model performance across ​​subject consistency, naturalness, and text alignment​​ ✔
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🧠 Introducing ​​OpenS2V-Eval​​—the first ​​fine-grained S2V benchmark​​, with ​​180 multi-domain prompts + real/synthetic test pairs​​. We propose ​​NexusScore​​, ​​NaturalScore​​, and ​​GmeScore​​ to precisely quantify model performance across ​​subject consistency, naturalness, and text alignment​​ ✔
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📊 Using this framework, we conduct a ​​comprehensive evaluation of 16 leading S2V models​​, revealing their strengths/weaknesses in complex scenarios!
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📊 Using this framework, we conduct a ​​comprehensive evaluation of 16 leading S2V models​​, revealing their strengths/weaknesses in complex scenarios!
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🔥 ​​OpenS2V-5M dataset​​ now available! A ​​5.4M 720P HD​​ collection of ​​subject-text-video triplets​​, enabled by ​​cross-video association segmentation + multi-view synthesis​​ for ​​diverse subjects & high-quality annotations​​ 🚀
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🔥 ​​OpenS2V-5M dataset​​ now available! A ​​5.4M 720P HD​​ collection of ​​subject-text-video triplets​​, enabled by ​​cross-video association segmentation + multi-view synthesis​​ for ​​diverse subjects & high-quality annotations​​ 🚀
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​​All resources open-sourced​​: Paper, Code, Data, and Evaluation Tools 📄
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​​All resources open-sourced​​: Paper, Code, Data, and Evaluation Tools 📄
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Let's advance S2V research together! 💡
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Let's advance S2V research together! 💡
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🔗 ​​Links​​:
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🔗 ​​Links​​:
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Paper: 
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Paper: 
OpenS2V-Nexus: A Detailed Benchmark and Million-Scale Dataset for
  Subject-to-Video Generation (2505.20292)
https://huggingface.co/papers/2505.20292
2505.20292
paper
resource
https://huggingface.co/papers/2505.20292
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Code: 
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Code: 
https://github.com/PKU-YuanGroup/OpenS2V-Nexus
https://github.com/PKU-YuanGroup/OpenS2V-Nexus
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Project: 
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Project: 
https://pku-yuangroup.github.io/OpenS2V-Nexus
https://pku-yuangroup.github.io/OpenS2V-Nexus
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LeaderBoard: 
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LeaderBoard: 
https://huggingface.co/spaces/BestWishYsh/OpenS2V-Eval
BestWishYsh/OpenS2V-Eval
space
resource
https://huggingface.co/spaces/BestWishYsh/OpenS2V-Eval
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OpenS2V-Eval: 
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OpenS2V-Eval: 
https://huggingface.co/datasets/BestWishYsh/OpenS2V-Eval
BestWishYsh/OpenS2V-Eval
dataset
resource
https://huggingface.co/datasets/BestWishYsh/OpenS2V-Eval
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OpenS2V-5M: 
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OpenS2V-5M: 
https://huggingface.co/datasets/BestWishYsh/OpenS2V-5M
BestWishYsh/OpenS2V-5M
dataset
resource
https://huggingface.co/datasets/BestWishYsh/OpenS2V-5M
Introducing our new work: OpenS2V-Nexus: A Detailed Benchmark and Million-Scale Dataset for Subject-to-Video Generation​​ 🚀

We tackle the core challenges of ​​Subject-to-Video Generation (S2V)​​ by systematically building the first complete infrastructure—featuring an evaluation benchmark and a million-scale dataset! ✨

🧠 Introducing ​​OpenS2V-Eval​​—the first ​​fine-grained S2V benchmark​​, with ​​180 multi-domain prompts + real/synthetic test pairs​​. We propose ​​NexusScore​​, ​​NaturalScore​​, and ​​GmeScore​​ to precisely quantify model performance across ​​subject consistency, naturalness, and text alignment​​ ✔

📊 Using this framework, we conduct a ​​comprehensive evaluation of 16 leading S2V models​​, revealing their strengths/weaknesses in complex scenarios!

🔥 ​​OpenS2V-5M dataset​​ now available! A ​​5.4M 720P HD​​ collection of ​​subject-text-video triplets​​, enabled by ​​cross-video association segmentation + multi-view synthesis​​ for ​​diverse subjects & high-quality annotations​​ 🚀

​​All resources open-sourced​​: Paper, Code, Data, and Evaluation Tools 📄
Let's advance S2V research together! 💡

🔗 ​​Links​​:
Paper: https://huggingface.co/papers/2505.20292
Code: https://github.com/PKU-YuanGroup/OpenS2V-Nexus
Project: https://pku-yuangroup.github.io/OpenS2V-Nexus
LeaderBoard: https://huggingface.co/spaces/BestWishYsh/OpenS2V-Eval
OpenS2V-Eval: https://huggingface.co/datasets/BestWishYsh/OpenS2V-Eval
OpenS2V-5M: https://huggingface.co/datasets/BestWishYsh/OpenS2V-5M
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