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Destination intention estimation-based convolutional encoder-decoder for pedestrian trajectory multimodality forecast
Forecasting pedestrian trajectory is a vital area of research in smart urban mobility, which
can be applied to intelligent transportation and intelligent surveillance. Current approaches …
can be applied to intelligent transportation and intelligent surveillance. Current approaches …
[PDF][PDF] Enhancing trajectory prediction through selfsupervised waypoint distortion prediction
Trajectory prediction is an important task that involves modeling the indeterminate nature of
agents to forecast future trajectories given the observed trajectory sequences. The task of …
agents to forecast future trajectories given the observed trajectory sequences. The task of …
STI-TP: A Spatio-temporal interleaved model for multi-modal trajectory prediction of heterogeneous traffic agents
Y Xu, Q Jia, H Wang, C Ji, X Li, Y Li, F Chen - Computers and Electrical …, 2024 - Elsevier
Trajectory prediction for heterogeneous traffic agents in autonomous driving is a challenging
and crucial task. A large amount of research has laid a solid foundation for this field …
and crucial task. A large amount of research has laid a solid foundation for this field …
Ccf: Cross correcting framework for pedestrian trajectory prediction
Multibranch Attentive Transformer With Joint Temporal and Social Correlations for Traffic Agents Trajectory Prediction
Accurately predicting the future trajectories of traffic agents is paramount for autonomous
unmanned systems, such as self-driving cars and mobile robotics. Extracting abundant …
unmanned systems, such as self-driving cars and mobile robotics. Extracting abundant …
Temporal prediction model with context-aware data augmentation for robust visual reinforcement learning
X Yue, H Ge, X He, Y Hou - Neural Computing and Applications, 2024 - Springer
While reinforcement learning has shown promising abilities to solve continuous control tasks
from visual inputs, it remains a challenge to learn robust representations from high …
from visual inputs, it remains a challenge to learn robust representations from high …
Enhancing Trajectory Prediction through Self-Supervised Waypoint Noise Prediction
Trajectory prediction is an important task that involves modeling the indeterminate nature of
traffic actors to forecast future trajectories given the observed trajectory sequences …
traffic actors to forecast future trajectories given the observed trajectory sequences …