Road: The road event awareness dataset for autonomous driving
G Singh, S Akrigg, M Di Maio, V Fontana… - IEEE transactions on …, 2022 - ieeexplore.ieee.org
Humans drive in a holistic fashion which entails, in particular, understanding dynamic road
events and their evolution. Injecting these capabilities in autonomous vehicles can thus take …
events and their evolution. Injecting these capabilities in autonomous vehicles can thus take …
Ithaca365: Dataset and driving perception under repeated and challenging weather conditions
Advances in perception for self-driving cars have accelerated in recent years due to the
availability of large-scale datasets, typically collected at specific locations and under nice …
availability of large-scale datasets, typically collected at specific locations and under nice …
V2x-seq: A large-scale sequential dataset for vehicle-infrastructure cooperative perception and forecasting
Utilizing infrastructure and vehicle-side information to track and forecast the behaviors of
surrounding traffic participants can significantly improve decision-making and safety in …
surrounding traffic participants can significantly improve decision-making and safety in …
Reasonnet: End-to-end driving with temporal and global reasoning
The large-scale deployment of autonomous vehicles is yet to come, and one of the major
remaining challenges lies in urban dense traffic scenarios. In such cases, it remains …
remaining challenges lies in urban dense traffic scenarios. In such cases, it remains …
A large scale event-based detection dataset for automotive
P De Tournemire, D Nitti, E Perot, D Migliore… - arXiv preprint arXiv …, 2020 - arxiv.org
We introduce the first very large detection dataset for event cameras. The dataset is
composed of more than 39 hours of automotive recordings acquired with a 304x240 ATIS …
composed of more than 39 hours of automotive recordings acquired with a 304x240 ATIS …
Predicting vehicle behaviors over an extended horizon using behavior interaction network
Anticipating possible behaviors of traffic participants is an essential capability of
autonomous vehicles. Many behavior detection and maneuver recognition methods only …
autonomous vehicles. Many behavior detection and maneuver recognition methods only …
An efficient and scalable deep learning approach for road damage detection
S Naddaf-Sh, MM Naddaf-Sh… - … Conference on Big …, 2020 - ieeexplore.ieee.org
Pavement condition evaluation is essential to time the preventative or rehabilitative actions
and control distress propagation. Failing to conduct timely evaluations can lead to severe …
and control distress propagation. Failing to conduct timely evaluations can lead to severe …
Zenseact open dataset: A large-scale and diverse multimodal dataset for autonomous driving
Existing datasets for autonomous driving (AD) often lack diversity and long-range
capabilities, focusing instead on 360* perception and temporal reasoning. To address this …
capabilities, focusing instead on 360* perception and temporal reasoning. To address this …
DLT-Net: Joint detection of drivable areas, lane lines, and traffic objects
Perception is an essential task for self-driving cars, but most perception tasks are usually
handled independently. We propose a unified neural network named DLT-Net to detect …
handled independently. We propose a unified neural network named DLT-Net to detect …