Perception and sensing for autonomous vehicles under adverse weather conditions: A survey
Abstract Automated Driving Systems (ADS) open up a new domain for the automotive
industry and offer new possibilities for future transportation with higher efficiency and …
industry and offer new possibilities for future transportation with higher efficiency and …
A survey on approximate edge AI for energy efficient autonomous driving services
Autonomous driving services depends on active sensing from modules such as camera,
LiDAR, radar, and communication units. Traditionally, these modules process the sensed …
LiDAR, radar, and communication units. Traditionally, these modules process the sensed …
ACDC: The adverse conditions dataset with correspondences for semantic driving scene understanding
Level 5 autonomy for self-driving cars requires a robust visual perception system that can
parse input images under any visual condition. However, existing semantic segmentation …
parse input images under any visual condition. However, existing semantic segmentation …
SHIFT: a synthetic driving dataset for continuous multi-task domain adaptation
Adapting to a continuously evolving environment is a safety-critical challenge inevitably
faced by all autonomous-driving systems. Existing image-and video-based driving datasets …
faced by all autonomous-driving systems. Existing image-and video-based driving datasets …
Tartanair: A dataset to push the limits of visual slam
We present a challenging dataset, the TartanAir, for robot navigation tasks and more. The
data is collected in photo-realistic simulation environments with the presence of moving …
data is collected in photo-realistic simulation environments with the presence of moving …
Guided curriculum model adaptation and uncertainty-aware evaluation for semantic nighttime image segmentation
Most progress in semantic segmentation reports on daytime images taken under favorable
illumination conditions. We instead address the problem of semantic segmentation of …
illumination conditions. We instead address the problem of semantic segmentation of …
Wilddash-creating hazard-aware benchmarks
Test datasets should contain many different challenging aspects so that the robustness and
real-world applicability of algorithms can be assessed. In this work, we present a new test …
real-world applicability of algorithms can be assessed. In this work, we present a new test …
Map-guided curriculum domain adaptation and uncertainty-aware evaluation for semantic nighttime image segmentation
We address the problem of semantic nighttime image segmentation and improve the state-of-
the-art, by adapting daytime models to nighttime without using nighttime annotations …
the-art, by adapting daytime models to nighttime without using nighttime annotations …
Object detection in adverse weather for autonomous driving through data merging and YOLOv8
D Kumar, N Muhammad - Sensors, 2023 - mdpi.com
For autonomous driving, perception is a primary and essential element that fundamentally
deals with the insight into the ego vehicle's environment through sensors. Perception is …
deals with the insight into the ego vehicle's environment through sensors. Perception is …
Unifying panoptic segmentation for autonomous driving
O Zendel, M Schörghuber, B Rainer… - Proceedings of the …, 2022 - openaccess.thecvf.com
This paper aims to improve panoptic segmentation for real-world applications in three ways.
First, we present a label policy that unifies four of the most popular panoptic segmentation …
First, we present a label policy that unifies four of the most popular panoptic segmentation …