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 5351–5375 of 6092 papers

TitleStatusHype
IDDA: a large-scale multi-domain dataset for autonomous driving—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
Interpretable Safety Validation for Autonomous VehiclesCode0
A2D2: Audi Autonomous Driving Dataset—0
Adversarial Evaluation of Autonomous Vehicles in Lane-Change Scenarios—0
ASL Recognition with Metric-Learning based Lightweight Network—0
Deep Learning for Image and Point Cloud Fusion in Autonomous Driving: A Review—0
Scalable Active Learning for Object Detection—0
DMLO: Deep Matching LiDAR Odometry—0
Scenario-Transferable Semantic Graph Reasoning for Interaction-Aware Probabilistic Prediction—0
How Do You Act? An Empirical Study to Understand Behavior of Deep Reinforcement Learning Agents—0
Depth Sensing Beyond LiDAR Range—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
DOPS: Learning to Detect 3D Objects and Predict their 3D Shapes—0
Map-Enhanced Ego-Lane Detection in the Missing Feature Scenarios—0
Under the Hood of Neural Networks: Characterizing Learned Representations by Functional Neuron Populations and Network Ablations—0
Extraction and Assessment of Naturalistic Human Driving Trajectories from Infrastructure Camera and Radar Sensors—0
Physically Realizable Adversarial Examples for LiDAR Object Detection—0
Shared Cross-Modal Trajectory Prediction 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