arXiv上今年8月文章“TNT: Target-driveN Trajectory Prediction“,是关于谷歌WAYMO的轨迹预测方法。被会议CoRL(Conference on Robot Learning)‘2020录取。 TNT是一种基于历史数据(即多代理和环境之间交互)生成目标的轨迹状态序列方法,并基于似然估计得到紧凑的轨迹预测集。不同于以前方法,即基于定义的潜变量并依赖于测...
DenseTNT: End-to-end Trajectory Prediction from Dense Goal Sets 一、摘要由于人类行为的随机性,预测道路智能体的未来轨迹对自动驾驶具有挑战性。近年来,基于目标的多轨迹预测方法被证明是有效的,该方法首先对超过采样的目标候选对象进行评分,然后从中… 小齐发表于机器学习文... 【轨迹预测系列】【笔记】DenseTNT...
Target-driven是一种以目标为导向的方法或框架,广泛应用于轨迹预测、决策制定和任务执行等领域。其核心思想是通过明确的目标设定来指导后续的预测、规划和行动,从而提高结果的准确性和可解释性。在轨迹预测领域,典型的应用是TNT(Target-driveN Trajectory Prediction)框架,它通过目标预测、目标条...
A Python and Pytorch implementation ofTNT: Target-driveN Trajectory PredictionandVectorNet: Encoding HD Maps and Agent Dynamics from Vectorized Representation. ATTENTION: Currently, the training consumes a large memory (128G+) since an in-memory data loader is implemented. We'll provide a new dataloa...
We investigated as many combinations as possible to prove that our chosen target points and the number of rounds for trajectory prediction are optimal. Targets Iterations minADE6↓ minFDE6↓ MR6↓ 1 1 0.74 1.33 0.17 1 3 0.74 1.33 0.17 1 6 0.74 1.32 0.17 3 3 0.70 1.24 0.15 3 6 0.70 ...
This resonates intriguingly with the clinical implications, especially mirroring the learning trajectory and characteristics of clinical experts. In the clinical training of experts, reliance is placed on multimodality information; learning is not confined to either images or text but is rather a ...
The rapid spread of SARS-CoV-2 required immediate actions to control the transmission of the virus and minimize its impact on humanity. An extensive mutation rate of this viral genome contributes to the virus’ ability to quickly adapt to environmental c
The trajectory clustering method (described in the Section 3.2) was used to retrieve the most populated geometries for further calculations. Simulation Interaction Diagram and Simulation Event Analyses were used to evaluate root-mean-square deviations (RMSD), root-mean-square fluctuations (RMSF), and ...