Code for "Transformer Networks for Trajectory Forecasting". PDF Latent Variable Sequential Set Transformers for Joint Multi-agent ... To this end, we propose a new Transformer, termed AgentFormer, that simultaneously models the time and social dimensions. PDF Multimodal Transformer Networks for Pedestrian Trajectory Prediction [2003.08111] Transformer Networks for Trajectory Forecasting PDF Adaptive Trajectory Prediction via Transferable GNN 3.1 Overview In this section, we introduce the proposed spatio-temporal graph Transformer based trajectory prediction framework, STAR. Based on the . Vehicles' trajectory prediction is a topic with growing interest in recent years, as there are applications in several domains ranging from autonomous driving to traffic congestion prediction and urban planning. Un-like these methods that use transformer as a part of their feature extractor, a fully transformer based architecture is used in our case to solve the multimodal motion prediction problem. Abstract: We propose a novel framework for multi-person 3D motion trajectory prediction. Joint Hand Motion and Interaction Hotspots Prediction from Egocentric ... Zhao et al. 2021自动驾驶论文总览（Cvpr+Icra+Iros） - 知乎 Analysis of pedestrians' motion is important to real-world applications in public scenes. TrAISformer-A generative transformer for AIS trajectory prediction Latent Variable Sequential Set Transformers for Joint Multi-Agent ... Trajectory Prediction for Autonomous Driving Using Spatial-Temporal ... To predict future trajectories, interactions between surrounding traffic are needed to be modelled. The latent intent of all . Keywords: trajectory prediction, motion forecasting, multi-task learning, attention, autonomous vehicles; Abstract: Predicting the motion of multiple agents is necessary for planning in dynamic environments. Transformer has demonstrated outstanding performance in dealing with sequential data. In practice, the prediction of aircraft trajectories needs to consider the impact of various sources, such as environmental conditions, pilot/controller behaviors, and potential conflicts with nearby aircraft. Our model performs hand and object interaction reasoning via the self-attention mechanism in Transformers. These are "simple" model because each person is modelled separately without any complex human-human nor scene interaction terms. Transformer based trajectory prediction | DeepAI