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We propose perceiver with register queries (perreg+), a novel trajectory prediction framework that introduces Given a query trajectory t and a trajectory dataset d, this task finds the trajectory t ∈ d that is the most similar to t. 本文提出了一种新的轨迹聚类方法，通过学习轨迹数据的空间和时间不变表示，解决传统方法在不同区域和时间段下聚类效果不佳的问题。 使用滑动窗口提取运动特征，并利用自动编码器.

We propose the first deep learning approach to learning representations of trajectories that is robust to low data quality, thus supporting accurate and efficient trajectory similarity. 我们提出了一个深度时空轨迹聚类（Deep Spatiotemporal Trajectory Clustering，DSTC）框架，以解决时空轨迹表示学习到友好的空间（Spatiotemporal Trajectory. Implementation of learning deep representation for trajectory clustering

This is not the official implementation

The code is implemented as one competitor of trajectory similarity learning. Overall, red adopts the transformer as the backbone.

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