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HuggingFace Daily Papers(社区热门论文)· HuggingFace Daily Papers(社区热门论文)·· 2026-04-15精选AI 评分71

Seedance 2.0:推进面向复杂世界的视频生成

AI 导读

Seedance 2.0于2026年2月初在国内发布,作为原生多模态音视频生成模型,采用统一高效架构支持文本、图像、音频、视频四种输入。可生成4-15秒、480p/720p音视频,开放平台支持3视频+9图像+3音频的多模态参考,并提供Fast加速版本。相比前代全面提升基础生成与多模态性能,专家评估显示其已达行业领先水平。

推荐理由

Seedance 2.0 把音视频联合生成真正推到了可用级别,支持多片段、多图片、多音频参考输入,对做视频的创作者是直接的生产力提升。

正文

Authors:Team Seedance, De Chen, Liyang Chen, Xin Chen, Ying Chen, Zhuo Chen, Zhuowei Chen, Feng Cheng, Tianheng Cheng, Yufeng Cheng, Mojie Chi, Xuyan Chi, Jian Cong, Qinpeng Cui, Fei Ding, Qide Dong, Yujiao Du, Haojie Duanmu, Junliang Fan, Jiarui Fang, Jing Fang, Zetao Fang, Chengjian Feng, Yu Gao, Diandian Gu, Dong Guo, Hanzhong Guo, Qiushan Guo, Boyang Hao, Hongxiang Hao, Haoxun He, Jiaao He, Qian He, Tuyen Hoang, Heng Hu, Ruoqing Hu, Yuxiang Hu, Jiancheng Huang, Weilin Huang, Zhaoyang Huang, Zhongyi Huang, Jishuo Jin, Ming Jing, Ashley Kim, Shanshan Lao, Yichong Leng, Bingchuan Li, Gen Li, Haifeng Li, Huixia Li, Jiashi Li, Ming Li, Xiaojie Li, Xingxing Li, Yameng Li, Yiying Li, Yu Li, Yueyan Li, Chao Liang, Han Liang, Jianzhong Liang, Ying Liang, Wang Liao, J. H. Lien, Shanchuan Lin, Xi Lin, Feng Ling, Yue Ling, Fangfang Liu, Jiawei Liu, Jihao Liu, Jingtuo Liu, Shu Liu, Sichao Liu, Wei Liu, Xue Liu, Zuxi Liu, Ruijie Lu, Lecheng Lyu, Jingting Ma, Tianxiang Ma, Xiaonan Nie, Jingzhe Ning, Junjie Pan, Xitong Pan, Ronggui Peng, Xueqiong Qu, Yuxi Ren, Yuchen Shen, Guang Shi, Lei Shi, Yinglong Song, Fan Sun, Li Sun, Renfei Sun, Wenjing Tang, Boyang Tao, Zirui Tao, Dongliang Wang, Feng Wang

et al. (71 additional authors not shown)

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Abstract:Seedance 2.0 is a new native multi-modal audio-video generation model, officially released in China in early February 2026. Compared with its predecessors, Seedance 1.0 and 1.5 Pro, Seedance 2.0 adopts a unified, highly efficient, and large-scale architecture for multi-modal audio-video joint generation. This allows it to support four input modalities: text, image, audio, and video, by integrating one of the most comprehensive suites of multi-modal content reference and editing capabilities available in the industry to date. It delivers substantial, well-rounded improvements across all key sub-dimensions of video and audio generation. In both expert evaluations and public user tests, the model has demonstrated performance on par with the leading levels in the field. Seedance 2.0 supports direct generation of audio-video content with durations ranging from 4 to 15 seconds, with native output resolutions of 480p and 720p. For multi-modal inputs as reference, its current open platform supports up to 3 video clips, 9 images, and 3 audio clips. In addition, we provide Seedance 2.0 Fast version, an accelerated variant of Seedance 2.0 designed to boost generation speed for low-latency scenarios. Seedance 2.0 has delivered significant improvements to its foundational generation capabilities and multi-modal generation performance, bringing an enhanced creative experience for end users.
Comments: Seedance 2.0 Model Card
Subjects: Computer Vision and Pattern Recognition (cs.CV)
Cite as: arXiv:2604.14148 [cs.CV]
  (or arXiv:2604.14148v1 [cs.CV] for this version)
  https://doi.org/10.48550/arXiv.2604.14148

arXiv-issued DOI via DataCite

Submission history

From: Jie Wu [view email]
[v1] Wed, 15 Apr 2026 17:59:40 UTC (4,950 KB)

来源:HuggingFace Daily Papers(社区热门论文) · arxiv.org