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English(EN) FloodDiffusion 2: Efficient and Path Controllable Streaming Motion Generation

FloodDiffusion 2 以效率和路径控制推进流式运动生成

研究人员推出了 FloodDiffusion 2 (FD2),一个专为高效且可控的流式运动生成设计的先进框架。该新模型在前代 FloodDiffusion (FD1) 的基础上,解决了效率和精确轨迹控制方面的局限性。FD2 采用了部分注意力机制以加快推理和训练速度,使用 Bregman 准则进行回归损失以保持运动质量,并结合精确的路径条件来引导角色沿期望轨迹移动。这些改进显著减少了训练计算和去噪时间,并在 SEED 和 HumanML3D 等基准测试中取得了最先进的性能。 AI

影响 提高了 AI 驱动的运动生成的效率和可控性,可能对动画和机器人技术产生影响。

排序理由 该集群包含一篇详细介绍新模型及其技术进步的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CV 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

FloodDiffusion 2 以效率和路径控制推进流式运动生成

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该集群包含一篇详细介绍新模型及其技术进步的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]
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完整方法见我们的编辑标准。

报道来源 [1]

  1. arXiv cs.CV TIER_1 English(EN) · Yiyi Cai, Yuhan Wu, Kunhang Li, Tu Fangyuan, Xiangyue Zhang, Qiaoge Li, Zhixiang Wang, Kaipeng Zhang, Haiyang Liu ·

    FloodDiffusion 2:高效且路径可控的流式运动生成

    arXiv:2609.33167v2 Announce Type: replace Abstract: We present FloodDiffusion 2 (FD2), an efficient and controllable framework that builds upon FloodDiffusion (FD1), a state-of-the-art streaming motion generation model. While FD1 produces plausible motion, it suffers from low eff…