In the concurrent work Scene Transformer[22], they used Transformer for both spatial and temporal dimension, adopted mask strategies and done . We question the use of the LSTM models and propose the novel use of Transformer Networks for trajectory forecasting. Transformer for Partial Differential Equations' Operator Learning Trajectory Transformer The model is formed indirectly by successively increasing the complexity of the demanded inference tasks. 第一名：Multi-Modal Interactive Agent Trajectory Prediction Using Heterogeneous Edge-Enhanced Graph Attention Network 【参见（第二周第3 . Our model has three components: a Transformer-based module for taking the pedestrians' historical trajectory as input, we call it the encoder part, a Social-Attention-based module for capturing the spatial correlations of interactions, and a Transformer-based module for output the predicted trajectory of every pedestrian, which is a decoder part. For pedestrian trajectory prediction, the number of pedestrians in one frame is in the scale of about hundred. We evaluate VPT360 over three widely-used . Zhao et al. Multimodal Motion Prediction with Stacked Transformers Spatio-Temporal Graph Transformer Networks for Pedestrian Trajectory ... A Spatio-temporal Transformer for 3D Human Motion Prediction Mapping Intimacies . In this paper, we present STAR, a Spatio-Temporal grAph tRansformer framework, which tackles trajectory prediction by only attention mechanisms. Multi-Person 3D Motion Prediction with Multi-Range Transformers TrAISformer-A generative transformer for AIS trajectory prediction Then, we induce the multimodality via a . Sequence Modeling Solutions - The Berkeley Artificial Intelligence ... When minimizing the symmetric cross-entropy, previ-ous approaches [34,38] usually make use of the normal-izing ow, which transforms a simple Gaussian distribution into the target trajectory distribution through a sequence of auto-regressive mappings. For the next POI prediction task, ST-RNN . Meanwhile, a Transformer encoder is applied in our method to extract the temporal information from the fused feature sequence. A Transformer [31]-based mobility feature extractor is a fundamental component in MobTCastto perform the main POI prediction task. ICCV 2021 •Tokens are permutation-invariant in self-attention (no order of information) .
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