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 5276–5300 of 6092 papers

TitleStatusHype
Occluded Prohibited Items Detection: an X-ray Security Inspection Benchmark and De-occlusion Attention ModuleCode1
Efficient Synthesis of Compact Deep Neural Networks—0
IDDA: a large-scale multi-domain dataset for autonomous driving—0
Approximate Inverse Reinforcement Learning from Vision-based Imitation Learning—0
Knowledge Distillation for Action Anticipation via Label Smoothing—0
Mosaic Super-resolution via Sequential Feature Pyramid Networks—0
Scalable Autonomous Vehicle Safety Validation through Dynamic Programming and Scene Decomposition—0
A2D2: Audi Autonomous Driving Dataset—0
Interpretable Safety Validation for Autonomous VehiclesCode0
Adversarial Evaluation of Autonomous Vehicles in Lane-Change Scenarios—0
Toward Hierarchical Self-Supervised Monocular Absolute Depth Estimation for Autonomous Driving ApplicationsCode1
Deep Learning for Image and Point Cloud Fusion in Autonomous Driving: A Review—0
ASL Recognition with Metric-Learning based Lightweight Network—0
TOG: Targeted Adversarial Objectness Gradient Attacks on Real-time Object Detection SystemsCode1
Scalable Active Learning for Object Detection—0
DMLO: Deep Matching LiDAR Odometry—0
End-to-End Pseudo-LiDAR for Image-Based 3D Object DetectionCode1
Scenario-Transferable Semantic Graph Reasoning for Interaction-Aware Probabilistic Prediction—0
Depth Sensing Beyond LiDAR Range—0
How Do You Act? An Empirical Study to Understand Behavior of Deep Reinforcement Learning Agents—0
CVPR 2019 WAD Challenge on Trajectory Prediction and 3D Perception—0
Reconfigurable Voxels: A New Representation for LiDAR-Based Point Clouds—0
MNEW: Multi-domain Neighborhood Embedding and Weighting for Sparse Point Clouds Segmentation—0
Minimizing Age-of-Information for Fog Computing-supported Vehicular Networks with Deep Q-learning—0
Two-Stream AMTnet for Action DetectionCode0
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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