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 5101–5150 of 6092 papers

TitleStatusHype
Distance-Normalized Unified Representation for Monocular 3D Object Detection—0
Modeling the Effects of Windshield Refraction for Camera Calibration—0
Polynomial Regression Network for Variable-Number Lane Detection—0
Diverse and Admissible Trajectory Prediction through Multimodal Context UnderstandingCode1
PanoNet: Real-time Panoptic Segmentation through Position-Sensitive Feature Embedding—0
Learning to Rank for Active Learning: A Listwise Approach—0
Traffic Control Gesture Recognition for Autonomous VehiclesCode1
Deep Traffic Sign Detection and Recognition Without Target Domain Real Images—0
LevelSet R-CNN: A Deep Variational Method for Instance Segmentation—0
Heatmap-based Vanishing Point boosts Lane Detection—0
Speed-up Heuristic for an On-Demand Ride-Pooling Algorithm—0
Online Visual Place Recognition via Saliency Re-identificationCode1
BiTraP: Bi-directional Pedestrian Trajectory Prediction with Multi-modal Goal EstimationCode1
Simultaneously Learning Corrections and Error Models for Geometry-based Visual Odometry Methods—0
A Deep Learning Framework for Generation and Analysis of Driving Scenario Trajectories—0
S^3Net: Semantic-Aware Self-supervised Depth Estimation with Monocular Videos and Synthetic Data—0
Robust Ego and Object 6-DoF Motion Estimation and TrackingCode1
YOLOpeds: Efficient Real-Time Single-Shot Pedestrian Detection for Smart Camera Applications—0
GSNet: Joint Vehicle Pose and Shape Reconstruction with Geometrical and Scene-aware SupervisionCode1
Crowdsourced 3D Mapping: A Combined Multi-View Geometry and Self-Supervised Learning ApproachCode1
Applying Semantic Segmentation to Autonomous Cars in the Snowy Environment—0
Grid-Based Stochastic Model Predictive Control for Trajectory Planning in Uncertain Environments—0
An LSTM Approach to Temporal 3D Object Detection in LiDAR Point Clouds—0
Enhanced Transfer Learning for Autonomous Driving with Systematic Accident Simulation—0
CurveLane-NAS: Unifying Lane-Sensitive Architecture Search and Adaptive Point BlendingCode1
Polylidar3D -- Fast Polygon Extraction from 3D DataCode1
Scaling Polyhedral Neural Network Verification on GPUs—0
Pillar-based Object Detection for Autonomous DrivingCode1
Understanding and Mitigating the Limitations of Prioritized Experience ReplayCode0
DVI: Depth Guided Video Inpainting for Autonomous DrivingCode1
PerMO: Perceiving More at Once from a Single Image for Autonomous Driving—0
openDD: A Large-Scale Roundabout Drone DatasetCode1
Decision-making Strategy on Highway for Autonomous Vehicles using Deep Reinforcement Learning—0
Accelerating Robustness Verification of Deep Neural Networks Guided by Target Labels—0
InfoFocus: 3D Object Detection for Autonomous Driving with Dynamic Information Modeling—0
CenterNet3D: An Anchor Free Object Detector for Point CloudCode1
Probabilistic Jacobian-based Saliency Maps AttacksCode1
SkyScapes -- Fine-Grained Semantic Understanding of Aerial Scenes—0
A Quick Review on Recent Trends in 3D Point Cloud Data Compression Techniques and the Challenges of Direct Processing in 3D Compressed Domain—0
Deformable spatial propagation network for depth completion—0
KIT MOMA: A Mobile Machines Dataset—0
Synthetic-to-Real Domain Adaptation for Lane Detection—0
PathGAN: Local Path Planning with Attentive Generative Adversarial NetworksCode0
Enable an Open Software Defined Mobility Ecosystem through VEC-OF—0
Single Shot MC Dropout ApproximationCode1
Wasserstein Distances for Stereo Disparity EstimationCode1
Model-based Exploration of the Frontier of Behaviours for Deep Learning System TestingCode1
Traffic Agent Trajectory Prediction Using Social Convolution and Attention Mechanism—0
Deep Neural Networks with Koopman Operators for Modeling and Control of Autonomous Vehicles—0
DepthNet: Real-Time LiDAR Point Cloud Depth Completion for Autonomous VehiclesCode0
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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