V2v4real: A real-world large-scale dataset for vehicle-to-vehicle cooperative perception
Modern perception systems of autonomous vehicles are known to be sensitive to occlusions
and lack the capability of long perceiving range. It has been one of the key bottlenecks that …
and lack the capability of long perceiving range. It has been one of the key bottlenecks that …
Embodiedscan: A holistic multi-modal 3d perception suite towards embodied ai
In the realm of computer vision and robotics embodied agents are expected to explore their
environment and carry out human instructions. This necessitates the ability to fully …
environment and carry out human instructions. This necessitates the ability to fully …
Domain adaptive object detection for autonomous driving under foggy weather
Most object detection methods for autonomous driving usually assume a onsistent feature
distribution between training and testing data, which is not always the case when weathers …
distribution between training and testing data, which is not always the case when weathers …
V2x-real: a largs-scale dataset for vehicle-to-everything cooperative perception
Recent advancements in Vehicle-to-Everything (V2X) technologies have enabled
autonomous vehicles to share sensing information to see through occlusions, greatly …
autonomous vehicles to share sensing information to see through occlusions, greatly …
Tumtraf v2x cooperative perception dataset
Cooperative perception offers several benefits for enhancing the capabilities of autonomous
vehicles and improving road safety. Using roadside sensors in addition to onboard sensors …
vehicles and improving road safety. Using roadside sensors in addition to onboard sensors …
VIPS: Real-time perception fusion for infrastructure-assisted autonomous driving
Infrastructure-assisted autonomous driving is an emerging paradigm that expects to
significantly improve the driving safety of autonomous vehicles. The key enabling …
significantly improve the driving safety of autonomous vehicles. The key enabling …
Joint multi-object detection and tracking with camera-LiDAR fusion for autonomous driving
K Huang, Q Hao - 2021 IEEE/RSJ International Conference on …, 2021 - ieeexplore.ieee.org
Multi-object tracking (MOT) with camera-LiDAR fusion demands accurate results of object
detection, affinity computation and data association in real time. This paper presents an …
detection, affinity computation and data association in real time. This paper presents an …
A survey on autonomous driving datasets: Data statistic, annotation, and outlook
Autonomous driving has rapidly developed and shown promising performance with recent
advances in hardware and deep learning methods. High-quality datasets are fundamental …
advances in hardware and deep learning methods. High-quality datasets are fundamental …
A survey on autonomous driving datasets: Statistics, annotation quality, and a future outlook
Autonomous driving has rapidly developed and shown promising performance due to recent
advances in hardware and deep learning techniques. High-quality datasets are fundamental …
advances in hardware and deep learning techniques. High-quality datasets are fundamental …
Point wise or feature wise? A benchmark comparison of publicly available LiDAR odometry algorithms in urban canyons
Robust and precise localization is essential for an autonomous system with navigation
requirements. Lidar odometry (LO) has been extensively studied in the past decades to …
requirements. Lidar odometry (LO) has been extensively studied in the past decades to …