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

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Showing 5751–5775 of 6092 papers

TitleStatusHype
BLVD: Building A Large-scale 5D Semantics Benchmark for Autonomous DrivingCode0
SimpleDet: A Simple and Versatile Distributed Framework for Object Detection and Instance Recognition—0
Simple Physical Adversarial Examples against End-to-End Autonomous Driving Models—0
Exploring OpenStreetMap Availability for Driving Environment Understanding—0
Improved Robustness and Safety for Autonomous Vehicle Control with Adversarial Reinforcement Learning—0
Using DP Towards A Shortest Path Problem-Related Application—0
Revisiting the Evaluation of Uncertainty Estimation and Its Application to Explore Model Complexity-Uncertainty Trade-OffCode0
Selective Sensor Fusion for Neural Visual-Inertial Odometry—0
An Adversarial Super-Resolution Remedy for Radar Design Trade-offs—0
Online Vehicle Trajectory Prediction using Policy Anticipation Network and Optimization-based Context Reasoning—0
Budgeted Reinforcement Learning in Continuous State SpaceCode0
Visual-based Autonomous Driving Deployment from a Stochastic and Uncertainty-aware PerspectiveCode0
Stereo R-CNN based 3D Object Detection for Autonomous DrivingCode0
Capsule Neural Network based Height Classification using Low-Cost Automotive Ultrasonic Sensors—0
The importance of space and time in neuromorphic cognitive agents—0
SSA-CNN: Semantic Self-Attention CNN for Pedestrian Detection—0
A Driving Intention Prediction Method Based on Hidden Markov Model for Autonomous Driving—0
Towards Corner Case Detection for Autonomous Driving—0
An efficient solution for semantic segmentation: ShuffleNet V2 with atrous separable convolutionsCode0
Box-level Segmentation Supervised Deep Neural Networks for Accurate and Real-time Multispectral Pedestrian Detection—0
Situation-Aware Pedestrian Trajectory Prediction with Spatio-Temporal Attention Model—0
GAN- vs. JPEG2000 Image Compression for Distributed Automotive Perception: Higher Peak SNR Does Not Mean Better Semantic Segmentation—0
WiseMove: A Framework for Safe Deep Reinforcement Learning for Autonomous Driving—0
Semantic Label Reduction Techniques for Autonomous Driving—0
Yes, we GAN: Applying Adversarial Techniques for Autonomous Driving—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