Securing connected & autonomous vehicles: Challenges posed by adversarial machine learning and the way forward
Connected and autonomous vehicles (CAVs) will form the backbone of future next-
generation intelligent transportation systems (ITS) providing travel comfort, road safety …
generation intelligent transportation systems (ITS) providing travel comfort, road safety …
Surround-view fisheye camera perception for automated driving: Overview, survey & challenges
Surround-view fisheye cameras are commonly used for near-field sensing in automated
driving. Four fisheye cameras on four sides of the vehicle are sufficient to cover 360° around …
driving. Four fisheye cameras on four sides of the vehicle are sufficient to cover 360° around …
Woodscape: A multi-task, multi-camera fisheye dataset for autonomous driving
Fisheye cameras are commonly employed for obtaining a large field of view in surveillance,
augmented reality and in particular automotive applications. In spite of their prevalence …
augmented reality and in particular automotive applications. In spite of their prevalence …
Weather and light level classification for autonomous driving: Dataset, baseline and active learning
MM Dhananjaya, VR Kumar… - 2021 IEEE International …, 2021 - ieeexplore.ieee.org
Autonomous driving is rapidly advancing, and Level 2 functions are becoming a standard
feature. One of the foremost outstanding hurdles is to obtain robust visual perception in …
feature. One of the foremost outstanding hurdles is to obtain robust visual perception in …
Near-field perception for low-speed vehicle automation using surround-view fisheye cameras
Cameras are the primary sensor in automated driving systems. They provide high
information density and are optimal for detecting road infrastructure cues laid out for human …
information density and are optimal for detecting road infrastructure cues laid out for human …
Fisheyemodnet: Moving object detection on surround-view cameras for autonomous driving
Moving Object Detection (MOD) is an important task for achieving robust autonomous
driving. An autonomous vehicle has to estimate collision risk with other interacting objects in …
driving. An autonomous vehicle has to estimate collision risk with other interacting objects in …
Let's get dirty: Gan based data augmentation for camera lens soiling detection in autonomous driving
Wide-angle fisheye cameras are commonly used in automated driving for parking and low-
speed navigation tasks. Four of such cameras form a surround-view system that provides a …
speed navigation tasks. Four of such cameras form a surround-view system that provides a …
Navya3dseg-navya 3d semantic segmentation dataset design & split generation for autonomous vehicles
Autonomous driving (AD) perception today relies heavily on deep learning based
architectures requiring large scale annotated datasets with their associated costs for …
architectures requiring large scale annotated datasets with their associated costs for …
Tiledsoilingnet: Tile-level soiling detection on automotive surround-view cameras using coverage metric
Automotive cameras, particularly surround-view cameras, tend to get soiled by mud, water,
snow, etc. For higher levels of autonomous driving, it is necessary to have a soiling detection …
snow, etc. For higher levels of autonomous driving, it is necessary to have a soiling detection …
Deeptrailerassist: Deep learning based trailer detection, tracking and articulation angle estimation on automotive rear-view camera
Trailers are commonly used for transport of goods and recreational materials. Even for
experienced drivers, manoeuvres with trailers, especially reversing can be complex and …
experienced drivers, manoeuvres with trailers, especially reversing can be complex and …