content.raw: Introducing our new work: OpenS2V-Nexus: A Detailed Benchmark and Million-Scale Dataset for Subject-to-Video Generation​​ 🚀
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content.value: Introducing our new work: OpenS2V-Nexus: A Detailed Benchmark and Million-Scale Dataset for Subject-to-Video Generation​​ 🚀
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content.raw: 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! ✨
content.type: text
content.value: 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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content.raw: 🧠 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​​ ✔
content.type: text
content.value: 🧠 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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content.raw: 📊 Using this framework, we conduct a ​​comprehensive evaluation of 16 leading S2V models​​, revealing their strengths/weaknesses in complex scenarios!
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content.value: 📊 Using this framework, we conduct a ​​comprehensive evaluation of 16 leading S2V models​​, revealing their strengths/weaknesses in complex scenarios!
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content.raw: 🔥 ​​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​​ 🚀
content.type: text
content.value: 🔥 ​​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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content.raw: ​​All resources open-sourced​​: Paper, Code, Data, and Evaluation Tools 📄
content.type: text
content.value: ​​All resources open-sourced​​: Paper, Code, Data, and Evaluation Tools 📄
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content.raw: Let's advance S2V research together! 💡
content.type: text
content.value: Let's advance S2V research together! 💡
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content.raw: 🔗 ​​Links​​:
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content.value: 🔗 ​​Links​​:
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content.raw: Paper: 
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content.value: Paper: 
content.label: OpenS2V-Nexus: A Detailed Benchmark and Million-Scale Dataset for
    Subject-to-Video Generation (2505.20292)
content.raw: https://huggingface.co/papers/2505.20292
content.id: 2505.20292
content.type: paper
content.type: resource
content.url: https://huggingface.co/papers/2505.20292
content.type: new_line
content.raw: Code: 
content.type: text
content.value: Code: 
content.href: https://github.com/PKU-YuanGroup/OpenS2V-Nexus
content.raw: https://github.com/PKU-YuanGroup/OpenS2V-Nexus
content.type: link
content.type: new_line
content.raw: Project: 
content.type: text
content.value: Project: 
content.href: https://pku-yuangroup.github.io/OpenS2V-Nexus
content.raw: https://pku-yuangroup.github.io/OpenS2V-Nexus
content.type: link
content.type: new_line
content.raw: LeaderBoard: 
content.type: text
content.value: LeaderBoard: 
content.raw: https://huggingface.co/spaces/BestWishYsh/OpenS2V-Eval
content.id: BestWishYsh/OpenS2V-Eval
content.type: space
content.type: resource
content.url: https://huggingface.co/spaces/BestWishYsh/OpenS2V-Eval
content.type: new_line
content.raw: OpenS2V-Eval: 
content.type: text
content.value: OpenS2V-Eval: 
content.raw: https://huggingface.co/datasets/BestWishYsh/OpenS2V-Eval
content.id: BestWishYsh/OpenS2V-Eval
content.type: dataset
content.type: resource
content.url: https://huggingface.co/datasets/BestWishYsh/OpenS2V-Eval
content.type: new_line
content.raw: OpenS2V-5M: 
content.type: text
content.value: OpenS2V-5M: 
content.raw: https://huggingface.co/datasets/BestWishYsh/OpenS2V-5M
content.id: BestWishYsh/OpenS2V-5M
content.type: dataset
content.type: resource
content.url: https://huggingface.co/datasets/BestWishYsh/OpenS2V-5M
rawContent: 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
reactions.reaction: 🔥
reactions.users: BestWishYsh John6666 ggikroa2223 AdinaY dhruv3006
reactions.reaction: 🚀
reactions.users: BestWishYsh AdinaY dhruv3006
commentators._id: 63468720dd6d90d82ccf3450
commentators.avatarUrl: https://cdn-avatars.huggingface.co/v1/production/uploads/63468720dd6d90d82ccf3450/tVBFlmZNz8FRMkOrDaDID.jpeg
commentators.fullname: YSH
commentators.name: BestWishYsh
commentators.type: user