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 5051–5075 of 6092 papers

TitleStatusHype
Dependency Decomposition and a Reject Option for Explainable Models—0
π-ROAD: a Learn-as-You-Go Framework for On-Demand Emergency Slices in V2X Scenarios—0
Direct Depth Learning Network for Stereo Matching—0
Transfer Learning for Efficient Iterative Safety Validation—0
Long Term Motion Prediction Using KeyposesCode0
Amortized Q-learning with Model-based Action Proposals for Autonomous Driving on Highways—0
Computer Stereo Vision for Autonomous Driving—0
Cirrus: A Long-range Bi-pattern LiDAR Dataset—0
It's All Around You: Range-Guided Cylindrical Network for 3D Object Detection—0
Generalized Object Detection on Fisheye Cameras for Autonomous Driving: Dataset, Representations and Baseline—0
Radar Artifact Labeling Framework (RALF): Method for Plausible Radar Detections in Datasets—0
Deep Inverse Sensor Models as Priors for evidential Occupancy Mapping—0
Value Alignment VerificationCode0
Robust and Accurate Object Velocity Detection by Stereo Camera for Autonomous Driving—0
Financial Sentiment Analysis: An Investigation into Common Mistakes and Silver Bullets—0
Displacement-Invariant Cost Computation for Efficient Stereo Matching—0
A Customizable Dynamic Scenario Modeling and Data Generation Platform for Autonomous Driving—0
Multi-task GANs for Semantic Segmentation and Depth Completion with Cycle Consistency—0
Temporal-Channel Transformer for 3D Lidar-Based Video Object Detection in Autonomous Driving—0
The NEOLIX Open Dataset for Autonomous Driving—0
Provably-Robust Runtime Monitoring of Neuron Activation Patterns—0
On Adversarial Robustness of 3D Point Cloud Classification under Adaptive Attacks—0
Nudge Attacks on Point-Cloud DNNs—0
Dense open-set recognition with synthetic outliers generated by Real NVPCode0
MoNet: Motion-based Point Cloud Prediction Network—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