English(EN) Motion Equivariant Convolutional LSTM: When Motion Becomes a Gauge Symmetry

新的MELSTM架构在序列模型中实现运动等变性

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-22 04:00

研究人员开发了一种新颖的运动等变卷积LSTM（MELSTM），通过将运动作为规范对称性来增强序列建模。这种新架构旨在对速度随时间变化的运动具有等变性，而之前的模型仅限于恒定速度流。MELSTM在未来帧预测、基于运动的分类和动作识别等各种任务中展示了更高的准确性和泛化能力，在相同参数数量下优于现有的卷积LSTM。 AI

影响引入了一种新的序列建模架构方法，改进了对动态运动的处理，可能有利于视频分析和机器人等应用。

排序理由该集群描述了一篇详细介绍新模型架构的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

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arXiv cs.LG TIER_1 English(EN) · Vahid Hosseinzadeh, T. Anderson Keller, Michael Puthawala · 2026-10-22 04:00

Motion Equivariant Convolutional LSTM: When Motion Becomes a Gauge Symmetry

arXiv:2610.28771v1 Announce Type: new Abstract: Objects move, cameras pan, and weather drifts with the wind: much of what changes in sequential data is motion. Motion changes where things are, not what they are, and is therefore a symmetry of the data. Yet standard recurrent netw…

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Motion Equivariant Convolutional LSTM: When Motion Becomes a Gauge Symmetry

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