English(EN) WorldFlow: Joint Video and 3D Motion Prediction via Large-Scale Pretraining

WorldFlow模型通过大规模预训练联合预测视频和3D运动

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-31 04:00

研究人员推出了一种新颖的生成式世界模型WorldFlow，旨在联合预测未来的视频和3D轨迹。该模型利用了Transformer混合体骨干网络来同时处理这两种模态，并通过利用预训练的视频模型来增强物理动力学的预测能力。为了支持其开发和评估，WorldFlow在一个包含144万个样本的大型数据集上进行了训练，并使用新的WorldFlowBench基准进行了验证，该基准包含跨越不同领域的1678个样本。 AI

影响这项研究通过改进物理状态的预测，推动了具身智能的发展，可能对机器人和仿真环境产生影响。

排序理由该集群描述了一篇介绍新AI模型和基准的新研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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报道来源 [1]

arXiv cs.AI TIER_1 English(EN) · Yuhao Lu, Jiongxu Chen, Hexiang Wei, Jiajin Wu, Juelin Li, Mingjian Liang, Fan Yang, Zhuowei Liang, Zihao Liu, Zhennan Wang, Sheng Wang, Lin Shao · 2026-10-31 04:00

WorldFlow：通过大规模预训练进行联合视频和3D运动预测

arXiv:2610.39278v1 Announce Type: cross Abstract: Predicting future physical states stands as a central challenge in embodied intelligence. Existing video world models leave 3D dynamics implicit, action-based formulations remain tied to specific robot configurations, and 3D motio…

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报道来源 [1]

WorldFlow：通过大规模预训练进行联合视频和3D运动预测

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