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English(EN) SimpliHuMoN: Simplifying Human Motion Prediction

新研究推动多人和单人运动预测

两篇新研究论文提出了先进的人类运动预测方法。FlowMoP 利用条件流匹配框架为多个代理生成多样化的未来运动,在 CMU-Mocap 和 3DPW 等基准测试中优于确定性模型。SimpliHuMoN 是一个基于 Transformer 的模型,提供了一种简化的方法,在 Human3.6M 和 ETH-UCY 等数据集上的仅姿势、仅轨迹和组合预测任务中取得了最先进的结果。 AI

影响 运动预测的这些进步可以通过实现更真实和交互式的人类行为模拟来增强机器人、动画和虚拟现实中的应用。

排序理由 两篇 arXiv 论文详细介绍了人类运动预测的新方法。

在 arXiv cs.CV 阅读 →

AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →

新研究推动多人和单人运动预测

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两篇 arXiv 论文详细介绍了人类运动预测的新方法。
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报道来源 [2]

  1. arXiv cs.CV TIER_1 English(EN) · Aadya Agrawal, Ho Kei Cheng, Alexander Schwing ·

    FlowMoP:随机多人运动预测

    arXiv:2611.09882v1 Announce Type: new Abstract: Predicting the future motion of multiple people is inherently stochastic: the same observed history admits many plausible continuations depending on intent, coordination, and social context. Yet the dominant paradigm in multi-person…

  2. arXiv cs.CV TIER_1 English(EN) · Aadya Agrawal, Alexander Schwing ·

    SimpliHuMoN:简化人类运动预测

    arXiv:2603.04399v2 Announce Type: replace Abstract: Human motion prediction combines the tasks of trajectory forecasting and human pose prediction. For each of the two tasks, specialized models have been developed. Combining these models for holistic human motion prediction is no…