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 5901–5950 of 6092 papers

TitleStatusHype
3D-RCNN: Instance-Level 3D Object Reconstruction via Render-and-Compare—0
PeerNets: Exploiting Peer Wisdom Against Adversarial AttacksCode0
Foresee: Attentive Future Projections of Chaotic Road Environments with Online Training—0
Novel Video Prediction for Large-scale Scene using Optical Flow—0
Propagating Confidences through CNNs for Sparse Data RegressionCode0
Semantic Road Layout Understanding by Generative Adversarial Inpainting—0
What Face and Body Shapes Can Tell About Height—0
A Data-Driven Approach for Autonomous Motion Planning and Control in Off-Road Driving Scenarios—0
VisualBackProp for learning using privileged information with CNNs—0
End-to-end driving simulation via angle branched network—0
Scene Understanding Networks for Autonomous Driving based on Around View Monitoring System—0
Counterexample-Guided Data AugmentationCode0
Task Agnostic Robust Learning on Corrupt Outputs by Correlation-Guided Mixture Density NetworksCode0
Hu-Fu: Hardware and Software Collaborative Attack Framework against Neural Networks—0
DeLS-3D: Deep Localization and Segmentation with a 3D Semantic MapCode0
LMNet: Real-time Multiclass Object Detection on CPU using 3D LiDARCode0
Improving Predictive Uncertainty Estimation using Dropout -- Hamiltonian Monte Carlo—0
BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask LearningCode1
Loss-Calibrated Approximate Inference in Bayesian Neural NetworksCode0
A Mixed Classification-Regression Framework for 3D Pose Estimation from 2D ImagesCode0
Verisimilar Percept Sequences Tests for Autonomous Driving Intelligent Agent Assessment—0
Failure Prediction for Autonomous Driving—0
Improve Uncertainty Estimation for Unknown Classes in Bayesian Neural Networks with Semi-Supervised /One Set Classification—0
Localized Traffic Sign Detection with Multi-scale Deconvolution Networks—0
Interaction-Aware Probabilistic Behavior Prediction in Urban Environments—0
PANDA: Facilitating Usable AI Development—0
Driving Policy Transfer via Modularity and Abstraction—0
Adaptive Performance Assessment For Drivers Through Behavioral AdvantageCode0
Accurate Deep Direct Geo-Localization from Ground Imagery and Phone-Grade GPS—0
Simulation-based Adversarial Test Generation for Autonomous Vehicles with Machine Learning ComponentsCode0
Training a Binary Weight Object Detector by Knowledge Transfer for Autonomous Driving—0
Towards Safe Autonomous Driving: Capture Uncertainty in the Deep Neural Network For Lidar 3D Vehicle Detection—0
Trajectory Factory: Tracklet Cleaving and Re-connection by Deep Siamese Bi-GRU for Multiple Object Tracking—0
Sensing Hidden Vehicles by Exploiting Multi-Path V2V Transmission—0
Understanding Humans in Crowded Scenes: Deep Nested Adversarial Learning and A New Benchmark for Multi-Human ParsingCode0
Looking at Hands in Autonomous Vehicles: A ConvNet Approach using Part Affinity Fields—0
Low-Latency Video Semantic Segmentation—0
A LiDAR Point Cloud Generator: from a Virtual World to Autonomous Driving—0
Predictions of short-term driving intention using recurrent neural network on sequential data—0
Safe end-to-end imitation learning for model predictive control—0
A Systematic Comparison of Deep Learning Architectures in an Autonomous Vehicle—0
Monocular Depth Estimation by Learning from Heterogeneous Datasets—0
Aerial LaneNet: Lane Marking Semantic Segmentation in Aerial Imagery using Wavelet-Enhanced Cost-sensitive Symmetric Fully Convolutional Neural Networks—0
Learning to Cluster for Proposal-Free Instance SegmentationCode0
MergeNet: A Deep Net Architecture for Small Obstacle Discovery—0
Complex-YOLO: Real-time 3D Object Detection on Point CloudsCode2
The ApolloScape Open Dataset for Autonomous Driving and its ApplicationCode1
Aggregated Sparse Attention for Steering Angle Prediction—0
Using Convolutional Neural Networks for Determining Reticulocyte Percentage in Cats—0
Feature Selective Small Object Detection via Knowledge-based Recurrent Attentive Neural 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