SOTAVerified

Autonomous Driving

Autonomous driving is the task of driving a vehicle without human conduction.

Many of the state-of-the-art results can be found at more general task pages such as 3D Object Detection and Semantic Segmentation.

(Image credit: Exploring the Limitations of Behavior Cloning for Autonomous Driving)

Papers

Showing 35513575 of 6092 papers

TitleStatusHype
The ATLAS of Traffic Lights: A Reliable Perception Framework for Autonomous Driving0
The Attack Generator: A Systematic Approach Towards Constructing Adversarial Attacks0
The Compact Support Neural Network0
The Design of Informative Take-Over Requests for Semi-Autonomous Cyber-Physical Systems: Combining Spoken Language and Visual Icons in a Drone-Controller Setting0
The Devil is in the Details: Simple Remedies for Image-to-LiDAR Representation Learning0
The Devil is in the Task: Exploiting Reciprocal Appearance-Localization Features for Monocular 3D Object Detection0
The #DNN-Verification Problem: Counting Unsafe Inputs for Deep Neural Networks0
The global consensus on the risk management of autonomous driving0
The Greedy Dirichlet Process Filter - An Online Clustering Multi-Target Tracker0
The Impact of Different Backbone Architecture on Autonomous Vehicle Dataset0
The importance of space and time in neuromorphic cognitive agents0
The JPEG Pleno Learning-based Point Cloud Coding Standard: Serving Man and Machine0
The Meeseeks Mesh: Spatially Consistent 3D Adversarial Objects for BEV Detector0
The NEOLIX Open Dataset for Autonomous Driving0
The Past and Present of Imitation Learning: A Citation Chain Study0
The Pedestrian Patterns Dataset0
Exploring Thermal Images for Object Detection in Underexposure Regions for Autonomous Driving0
The RoboDrive Challenge: Drive Anytime Anywhere in Any Condition0
The Robust Semantic Segmentation UNCV2023 Challenge Results0
The SYNTHIA Dataset: A Large Collection of Synthetic Images for Semantic Segmentation of Urban Scenes0
The Translucent Patch: A Physical and Universal Attack on Object Detectors0
The Use of Multimodal Large Language Models to Detect Objects from Thermal Images: Transportation Applications0
The Virtuous Machine - Old Ethics for New Technology?0
The Vulnerability of Semantic Segmentation Networks to Adversarial Attacks in Autonomous Driving: Enhancing Extensive Environment Sensing0
The Why, When, and How to Use Active Learning in Large-Data-Driven 3D Object Detection for Safe Autonomous Driving: An Empirical Exploration0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ReasonNetDriving Score79.95Unverified
2InterFuserDriving Score76.18Unverified
3TCPDriving Score75.14Unverified
4TF++ WPDriving Score66.32Unverified
5Learning From All Vehicles (LAV)Driving Score61.85Unverified
6TransFuserDriving Score61.18Unverified
7TransFuser (Reproduced)Driving Score55.04Unverified
8TCP (Reproduced)Driving Score47.91Unverified
9Latent TransFuserDriving Score45.2Unverified
10GRIADDriving Score36.79Unverified
#ModelMetricClaimedVerifiedStatus
1Geometric FusionRC69.17Unverified
2TransFuserRC56.36Unverified
#ModelMetricClaimedVerifiedStatus
1Geometric FusionRC86.91Unverified
2TransFuserRC78.41Unverified