PDF Multimodal Motion Prediction With Stacked Transformers In B-STAR, trajectory prediction is achieved by interleaving the spatial Transformer and temporal Transformer into an encoder-decoder structure. To tackle this task, we first provide an automatic way to collect trajectory and hotspots labels on large-scale data. Multimodal Motion Prediction Framework Motion prediction aims to accurately predict the future Trajectory Prediction Transformer Network to predict Trajectories for traffic agents In realistic traffic scenarios, trajectory prediction is important to guarantee the safety of an autonomous vehicle. Joint Hand Motion and Interaction Hotspots Prediction from Egocentric ... Trajectory Transformer Our framework is built upon self-attention, cross-attention . The Multi-scale graph-transformer-based trajectory prediction method is an efficient model that have better capability to learn nonlinear patterns and provide more prominent results over the existing methods on three publically available datasets Apolloscape, Argoverse and Lyft. [2112.04350] Transformer based trajectory prediction A Spatio-temporal Transformer for 3D Human Motion Prediction Mapping Intimacies . Pedestrian Trajectory Prediction using Context-Augmented Transformer ... humans have the possibility to move in multiple directions at any given instant of time. We benchmark two instances of our approach, Trajformer-12 and Trajformer-24, with respectively 12 and 24 layers in the transformer encoder. applied to many time series prediction problems such as pedestrian trajectory prediction [1, 36] and traffic prediction [34]. Keywords: trajectory prediction, motion forecasting, transformers, latent variable models; Abstract: Robust multi-agent trajectory prediction is essential for the safe control of robotic systems. 10.1109/3dv53792.2021.00066 Our method outperforms all previous models for both trajectory prediction and intention prediction tasks on the JAAD dataset and PIE dataset. Transformer-Based Individual Travel Destination Prediction. Latent Variable Sequential Set Transformers for Joint Multi-Agent ... Reframing Reinforcement Learning as Sequence Modeling with Transformers? We can also inspect the Trajectory Transformer as if it were a standard language model. vanilla transformer to model the trajectory sequences. In this paper, we present STAR, a Spatio-Temporal grAph tRansformer framework, which tackles trajectory prediction by only attention mechanisms. This task is challenging for several reasons: in fact, the future motion depends on interactions among objects and interactions of the .