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 5401–5425 of 6092 papers

TitleStatusHype
A machine learning environment for evaluating autonomous driving software—0
Inferring Spatial Uncertainty in Object Detection—0
DA4AD: End-to-End Deep Attention-based Visual Localization for Autonomous Driving—0
Spherical formulation of moving object geometric constraints for monocular fisheye cameras—0
A Convolutional Neural Network for Point Cloud Instance Segmentation in Cluttered Scene Trained by Synthetic Data Without Color—0
Safe Mission Planning under Dynamical Uncertainties—0
Deep Neural Network Perception Models and Robust Autonomous Driving Systems—0
Analyzing Accuracy Loss in Randomized Smoothing Defenses—0
Few-Shot Relation Learning with Attention for EEG-based Motor Imagery Classification—0
Safe Reinforcement Learning for Autonomous Vehicles through Parallel Constrained Policy Optimization—0
Learning to Collide: An Adaptive Safety-Critical Scenarios Generating Method—0
3D Point Cloud Processing and Learning for Autonomous Driving—0
FLIC: Fast Lidar Image Clustering—0
HVNet: Hybrid Voxel Network for LiDAR Based 3D Object Detection—0
An Evaluation of Knowledge Graph Embeddings for Autonomous Driving Data: Experience and Practice—0
Human-Machine Collaboration for Automated Vehicles via an Intelligent Two-Phase Haptic Interface—0
Training Adversarial Agents to Exploit Weaknesses in Deep Control PoliciesCode0
TGGLines: A Robust Topological Graph Guided Line Segment Detector for Low Quality Binary Images—0
Pedestrian Models for Autonomous Driving Part I: Low-Level Models, from Sensing to Tracking—0
Robust-Adaptive Control of Linear Systems: beyond Quadratic Costs—0
Safe reinforcement learning for probabilistic reachability and safety specifications: A Lyapunov-based approachCode0
SemanticPOSS: A Point Cloud Dataset with Large Quantity of Dynamic Instances—0
Improving Generalization of Reinforcement Learning with Minimax Distributional Soft Actor-Critic—0
SegVoxelNet: Exploring Semantic Context and Depth-aware Features for 3D Vehicle Detection from Point Cloud—0
Adapting to Unseen Environments through Explicit Representation of Context—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