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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 5801–5825 of 6092 papers

TitleStatusHype
Visual Attention for Behavioral Cloning in Autonomous Driving—0
SADA: Semantic Adversarial Diagnostic Attacks for Autonomous ApplicationsCode0
Risk-averse Behavior Planning for Autonomous Driving under Uncertainty—0
Spatio-Temporal Action Graph NetworksCode0
Rigorous Agent Evaluation: An Adversarial Approach to Uncover Catastrophic Failures—0
Evaluating Bayesian Deep Learning Methods for Semantic SegmentationCode0
ApolloCar3D: A Large 3D Car Instance Understanding Benchmark for Autonomous Driving—0
Deep Reinforcement Learning for Autonomous DrivingCode0
Is it Safe to Drive? An Overview of Factors, Challenges, and Datasets for Driveability Assessment in Autonomous Driving—0
Calibrating Uncertainties in Object Localization Task—0
ShelfNet for Fast Semantic SegmentationCode0
Efficient Video Understanding via Layered Multi Frame-Rate Analysis—0
Seeing in the dark with recurrent convolutional neural networks—0
Urban Driving with Multi-Objective Deep Reinforcement LearningCode0
Simulated Autonomous Driving in a Realistic Driving Environment using Deep Reinforcement Learning and a Deterministic Finite State Machine—0
Exploit the Connectivity: Multi-Object Tracking with TrackletNetCode0
Augmented LiDAR Simulator for Autonomous Driving—0
Evaluation of deep neural networks for traffic sign detection systemsCode0
nn-dependability-kit: Engineering Neural Networks for Safety-Critical Autonomous Driving SystemsCode0
Evaluating Uncertainty Quantification in End-to-End Autonomous Driving Control—0
Optical Flow Based Background Subtraction with a Moving Camera: Application to Autonomous Driving—0
Orthogonal Policy Gradient and Autonomous Driving Application—0
The Greedy Dirichlet Process Filter - An Online Clustering Multi-Target Tracker—0
Deep Object-Centric Policies for Autonomous Driving—0
An Orchestrated Empirical Study on Deep Learning Frameworks and Platforms—0
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Benchmark Results

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