A survey on motion prediction and risk assessment for intelligent vehicles
With the objective to improve road safety, the automotive industry is moving toward more
“intelligent” vehicles. One of the major challenges is to detect dangerous situations and react …
“intelligent” vehicles. One of the major challenges is to detect dangerous situations and react …
Crowded scene analysis: A survey
Automated scene analysis has been a topic of great interest in computer vision and
cognitive science. Recently, with the growth of crowd phenomena in the real world, crowded …
cognitive science. Recently, with the growth of crowd phenomena in the real world, crowded …
Self-supervised attentive generative adversarial networks for video anomaly detection
Video anomaly detection (VAD) refers to the discrimination of unexpected events in videos.
The deep generative model (DGM)-based method learns the regular patterns on normal …
The deep generative model (DGM)-based method learns the regular patterns on normal …
Deep-anomaly: Fully convolutional neural network for fast anomaly detection in crowded scenes
The detection of abnormal behaviour in crowded scenes has to deal with many challenges.
This paper presents an efficient method for detection and localization of anomalies in …
This paper presents an efficient method for detection and localization of anomalies in …
Detecting anomalous events in videos by learning deep representations of appearance and motion
Anomalous event detection is of utmost importance in intelligent video surveillance.
Currently, most approaches for the automatic analysis of complex video scenes typically rely …
Currently, most approaches for the automatic analysis of complex video scenes typically rely …
CommonRoad: Composable benchmarks for motion planning on roads
M Althoff, M Koschi, S Manzinger - 2017 IEEE Intelligent …, 2017 - ieeexplore.ieee.org
Numerical experiments for motion planning of road vehicles require numerous components:
vehicle dynamics, a road network, static obstacles, dynamic obstacles and their movement …
vehicle dynamics, a road network, static obstacles, dynamic obstacles and their movement …
AI-TP: Attention-based interaction-aware trajectory prediction for autonomous driving
K Zhang, L Zhao, C Dong, L Wu… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Despite the advancements in the technologies of autonomous driving, it is still challenging to
study the safety of a self-driving vehicle. Trajectory prediction is one core function of an …
study the safety of a self-driving vehicle. Trajectory prediction is one core function of an …
State estimation and motion prediction of vehicles and vulnerable road users for cooperative autonomous driving: A survey
The recent progress in autonomous vehicle research and development has led to
increasingly widespread testing of fully autonomous vehicles on public roads, where …
increasingly widespread testing of fully autonomous vehicles on public roads, where …
Vessel pattern knowledge discovery from AIS data: A framework for anomaly detection and route prediction
G Pallotta, M Vespe, K Bryan - Entropy, 2013 - mdpi.com
Understanding maritime traffic patterns is key to Maritime Situational Awareness
applications, in particular, to classify and predict activities. Facilitated by the recent build-up …
applications, in particular, to classify and predict activities. Facilitated by the recent build-up …
Deep-cascade: Cascading 3d deep neural networks for fast anomaly detection and localization in crowded scenes
This paper proposes a fast and reliable method for anomaly detection and localization in
video data showing crowded scenes. Time-efficient anomaly localization is an ongoing …
video data showing crowded scenes. Time-efficient anomaly localization is an ongoing …