FineVideo 幕後秘辛：Hugging Face 如何打造高品質開源影片資料集
Original: FineVideo: behind the scenes
With the explosion of video generation and understanding models such as Sora and Gen-3, high-quality video training data has become a key…
Hugging Face 釋出全新開源影片資料集「FineVideo」的幕後製作過程。為了解決高品質影片數據稀缺的問題，該項目收錄了超過 4.3 萬部影片（約 3,400 小時），並提供高達 120 萬個詳細的影片與文字配對。文章深入探討了其自動化清理、場景分割與多模態模型標註的管線（Pipeline）設計，旨在為社群提供訓練下一代影片理解與生成模型（Video-LLM）的標準基石。
With the explosion of video generation and understanding models such as Sora and Gen-3, high-quality video training data has become a key battleground for major organizations — yet the open-source community has long lacked structured, richly annotated video datasets. Hugging Face's "FineVideo" was created specifically to address this gap.
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