Pedestrian intention prediction for autonomous vehicles: A comprehensive survey
Lately, Autonomous vehicles (AV) have been gaining traction globally owing to their huge
social, economic and environmental benefits. However, the rising safety apprehensions for …
social, economic and environmental benefits. However, the rising safety apprehensions for …
Scept: Scene-consistent, policy-based trajectory predictions for planning
Trajectory prediction is a critical functionality of autonomous systems that share
environments with uncontrolled agents, one prominent example being self-driving vehicles …
environments with uncontrolled agents, one prominent example being self-driving vehicles …
Dynamic-group-aware networks for multi-agent trajectory prediction with relational reasoning
Demystifying the interactions among multiple agents from their past trajectories is
fundamental to precise and interpretable trajectory prediction. However, previous works …
fundamental to precise and interpretable trajectory prediction. However, previous works …
Pedestrian crossing action recognition and trajectory prediction with 3d human keypoints
Accurate understanding and prediction of human behaviors are critical prerequisites for
autonomous vehicles, especially in highly dynamic and interactive scenarios such as …
autonomous vehicles, especially in highly dynamic and interactive scenarios such as …
Scene informer: Anchor-based occlusion inference and trajectory prediction in partially observable environments
Navigating complex and dynamic environments requires autonomous vehicles (AVs) to
reason about both visible and occluded regions. This involves predicting the future motion of …
reason about both visible and occluded regions. This involves predicting the future motion of …
Disentangled neural relational inference for interpretable motion prediction
Effective interaction modeling and behavior prediction of dynamic agents play a significant
role in interactive motion planning for autonomous robots. Although existing methods have …
role in interactive motion planning for autonomous robots. Although existing methods have …
Sonic: Safe social navigation with adaptive conformal inference and constrained reinforcement learning
Reinforcement Learning (RL) has enabled social robots to generate trajectories without
human-designed rules or interventions, which makes it more effective than hard-coded …
human-designed rules or interventions, which makes it more effective than hard-coded …
Important object identification with semi-supervised learning for autonomous driving
Accurate identification of important objects in the scene is a prerequisite for safe and high-
quality decision making and motion planning of intelligent agents (eg, autonomous vehicles) …
quality decision making and motion planning of intelligent agents (eg, autonomous vehicles) …
A comprehensive review of deep learning approaches for group activity analysis
G Zhang, Y Geng, ZG Gong - The Visual Computer, 2024 - Springer
The study of group activity analysis has garnered significant attention. Group activity offers a
unique perspective on the relationships between individuals, providing insights that …
unique perspective on the relationships between individuals, providing insights that …
Multi-Agent Dynamic Relational Reasoning for Social Robot Navigation
Social robot navigation can be helpful in various contexts of daily life but requires safe
human-robot interactions and efficient trajectory planning. While modeling pairwise relations …
human-robot interactions and efficient trajectory planning. While modeling pairwise relations …