Most automated driving systems comprise a diverse sensor set, including
...
Recent advances in 3D object detection (3DOD) have obtained remarkably s...
Optical flow estimation is a well-studied topic for automated driving
ap...
Bird's-eye-view (BEV) grid is a common representation for the perception...
Object detection is a comprehensively studied problem in autonomous driv...
Modern object detection architectures are moving towards employing
self-...
Spiking Neural Networks are a recent and new neural network design appro...
Generating a detailed near-field perceptual model of the environment is ...
The incentive for using Evolutionary Algorithms (EAs) for the automated
...
Shadows are frequently encountered natural phenomena that significantly
...
Surround-view cameras are a primary sensor for automated driving, used f...
While deep neural networks (DNNs) achieve impressive performance on
envi...
Moving object detection and segmentation is an essential task in the
Aut...
In this paper, we present a system for incrementally reconstructing a de...
We present the WoodScape fisheye semantic segmentation challenge for
aut...
Deep neural networks (DNNs) have accomplished impressive success in vari...
Detection of moving objects is a very important task in autonomous drivi...
Electric Vehicles are increasingly common, with inductive chargepads bei...
Pedestrian Detection is the most critical module of an Autonomous Drivin...
Manual annotation of soiling on surround view cameras is a very challeng...
Autonomous driving is rapidly advancing, and Level 2 functions are becom...
Vision-based driver assistance systems is one of the rapidly growing res...
Automated driving is an active area of research in both industry and
aca...
Moving object Detection (MOD) is a critical task in autonomous driving a...
Data augmentation is a key component of CNN based image recognition task...
LiDAR based 3D object detection is a crucial module in autonomous drivin...
A 360 perception of scene geometry is essential for automated driving,
n...
Cameras are the primary sensor in automated driving systems. They provid...
Keypoint detection and description is a commonly used building block in
...
Object detection is a comprehensively studied problem in autonomous driv...
Panoptic Segmentation aims to provide an understanding of background (st...
Moving object segmentation is a crucial task for autonomous vehicles as ...
State-of-the-art self-supervised learning approaches for monocular depth...
Single encoder-decoder methodologies for semantic segmentation are reach...
In classical computer vision, rectification is an integral part of multi...
Automotive cameras, particularly surround-view cameras, tend to get soil...
With the development of deep representation learning, the domain of
rein...
Deep multi-task networks are of particular interest for autonomous drivi...
Automated Parking is becoming a standard feature in modern vehicles. Exi...
Automated Parking is a low speed manoeuvring scenario which is quite
uns...
Cameras are getting more and more important in autonomous driving. Wide-...
Moving Object Detection (MOD) is a critical task for autonomous vehicles...
Moving object detection is a critical task for autonomous vehicles. As
d...
Fisheye cameras are commonly used in applications like autonomous drivin...
Moving Object Detection (MOD) is an important task for achieving robust
...
LiDAR has become a standard sensor for autonomous driving applications a...
Cameras are an essential part of sensor suite in autonomous driving.
Sur...
Fisheye cameras are commonly employed for obtaining a large field of vie...
Multi-task learning is commonly used in autonomous driving for solving
v...
Recently, realistic data augmentation using neural networks especially
g...