[translate] acaravans walls 有蓬卡车墙壁 [translate] adisl 烦恶 [translate] aDashboard insert indicator unit 仪表板插入物显示单位 [translate] areadi 读书 [translate] aA Survey of Vision-Based Trajectory Learning and Analysis for Surveillance 基于视觉的弹道学会和分析勘测为监视 [translate] ...
Moreover, a lot of networks or modules [17,18] are employed to obtain the corresponding activity semantics and scene semantics, respectively. Show abstract Pedestrian trajectory prediction with convolutional neural networks 2022, Pattern Recognition Show abstract A survey on deep learning tools dealing ...
[ICDE2023] A PyTorch implementation of Self-supervised Trajectory Representation Learning with Temporal Regularities and Travel Semantics Framework (START). transformerrepresentation-learningunsupervised-learningtrajectory-analysistrajectory-clusteringtrajectory-predictiontrajectory-similaritygraph-attention-networksself-supe...
The interaction between target vehicles and surrounding agents and obstacles is also significant for prediction. Drivers, for example, can only perceive their approximate location and estimate the speed of surrounding agents and obstacles. With limited perceived information, skilled drivers can make good ...
Trajectory data classification: A review [paper] A comprehensive survey on trajectory-based location prediction [paper] A survey on trajectory data management, analytics, and learning [paper] A survey on deep learning for human mobility [paper] Classifying spatial trajectories [paper] Traffic prediction...
The results show that the T-GCN prediction is more stable and better than other deep learning models. In addition, compared with other region division methods, the method of a top-down division of regions for privacy budget allocation and the addition of Laplace noise is relatively more robust...
In this paper we discuss a problem of automatic analysis of vehicles trajectories in the context of illegal movements. It is crucial to detect restricted or security critical behaviour on roads, especially for safety protection and fluent traffic. Here, we propose an vision-based algorithm for vehi...
This study presents a novel framework that integrates the universal jamming gripper (UG) with unmanned aerial vehicles (UAVs) to enable automated grasping with no human operator in the loop. Grounded in the principles of granular jamming, the UG exhibits
Human Motion Trajectory Prediction: A Survey, 2019. [paper] A literature review on the prediction of pedestrian behavior in urban scenarios, ITSC 2018. [paper] Survey on Vision-Based Path Prediction. [paper] Autonomous vehicles that interact with pedestrians: A survey of theory and practice. [pa...
To address this, a rock detection approach is proposed that fuses both geometric stereo and monocular model-based semantic vision. Finally, we present a driving energy prediction algorithm called VeeGer [22] that combines terrain classification and obstacle detection. The resource awareness comes from...