Computer vision for autonomous vehicles: Problems, datasets and state of the art
Recent years have witnessed enormous progress in AI-related fields such as computer
vision, machine learning, and autonomous vehicles. As with any rapidly growing field, it …
vision, machine learning, and autonomous vehicles. As with any rapidly growing field, it …
Investigations of object detection in images/videos using various deep learning techniques and embedded platforms—A comprehensive review
In recent years there has been remarkable progress in one computer vision application
area: object detection. One of the most challenging and fundamental problems in object …
area: object detection. One of the most challenging and fundamental problems in object …
Pseudo-lidar from visual depth estimation: Bridging the gap in 3d object detection for autonomous driving
Abstract 3D object detection is an essential task in autonomous driving. Recent techniques
excel with highly accurate detection rates, provided the 3D input data is obtained from …
excel with highly accurate detection rates, provided the 3D input data is obtained from …
A survey on 3d object detection methods for autonomous driving applications
An autonomous vehicle (AV) requires an accurate perception of its surrounding environment
to operate reliably. The perception system of an AV, which normally employs machine …
to operate reliably. The perception system of an AV, which normally employs machine …
Pseudo-lidar++: Accurate depth for 3d object detection in autonomous driving
Detecting objects such as cars and pedestrians in 3D plays an indispensable role in
autonomous driving. Existing approaches largely rely on expensive LiDAR sensors for …
autonomous driving. Existing approaches largely rely on expensive LiDAR sensors for …
Monopair: Monocular 3d object detection using pairwise spatial relationships
Monocular 3D object detection is an essential component in autonomous driving while
challenging to solve, especially for those occluded samples which are only partially visible …
challenging to solve, especially for those occluded samples which are only partially visible …
Orthographic feature transform for monocular 3d object detection
3D object detection from monocular images has proven to be an enormously challenging
task, with the performance of leading systems not yet achieving even 10\% of that of LiDAR …
task, with the performance of leading systems not yet achieving even 10\% of that of LiDAR …
End-to-end pseudo-lidar for image-based 3d object detection
Reliable and accurate 3D object detection is a necessity for safe autonomous driving.
Although LiDAR sensors can provide accurate 3D point cloud estimates of the environment …
Although LiDAR sensors can provide accurate 3D point cloud estimates of the environment …
Train in germany, test in the usa: Making 3d object detectors generalize
In the domain of autonomous driving, deep learning has substantially improved the 3D
object detection accuracy for LiDAR and stereo camera data alike. While deep networks are …
object detection accuracy for LiDAR and stereo camera data alike. While deep networks are …
Monocular 3d object detection: An extrinsic parameter free approach
Monocular 3D object detection is an important task in autonomous driving. It can be easily
intractable where there exists ego-car pose change wrt ground plane. This is common due …
intractable where there exists ego-car pose change wrt ground plane. This is common due …