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 5626–5650 of 6092 papers

TitleStatusHype
Quantifying the LiDAR Sim-to-Real Domain Shift: A Detailed Investigation Using Object Detectors and Analyzing Point Clouds at Target-LevelCode0
Quantile-based Maximum Likelihood Training for Outlier DetectionCode0
GaussianFusion: Gaussian-Based Multi-Sensor Fusion for End-to-End Autonomous DrivingCode0
Detection of False Positive and False Negative Samples in Semantic SegmentationCode0
Detect Closer Surfaces that can be Seen: New Modeling and Evaluation in Cross-domain 3D Object DetectionCode0
Retrieval-based Localization Based on Domain-invariant Feature Learning under Changing EnvironmentsCode0
Multispectral Pedestrian Detection via Simultaneous Detection and SegmentationCode0
ShelfNet for Fast Semantic SegmentationCode0
MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior PredictionCode0
Query-Efficient Imitation Learning for End-to-End Autonomous DrivingCode0
DESPOT: Online POMDP Planning with RegularizationCode0
GAMMA: A General Agent Motion Model for Autonomous DrivingCode0
G2D: from GTA to DataCode0
FuSSI-Net: Fusion of Spatio-temporal Skeletons for Intention Prediction NetworkCode0
Sequential Action-Induced Invariant Representation for Reinforcement LearningCode0
FusionRCNN: LiDAR-Camera Fusion for Two-stage 3D Object DetectionCode0
Multimodal Trajectory Predictions for Autonomous Driving using Deep Convolutional NetworksCode0
ChauffeurNet: Learning to Drive by Imitating the Best and Synthesizing the WorstCode0
Multimodal Trajectory Prediction for Autonomous Driving on Unstructured Roads using Deep Convolutional NetworkCode0
CHARMS: A Cognitive Hierarchical Agent for Reasoning and Motion Stylization in Autonomous DrivingCode0
Full-Resolution Residual Networks for Semantic Segmentation in Street ScenesCode0
FT-ClipAct: Resilience Analysis of Deep Neural Networks and Improving their Fault Tolerance using Clipped ActivationCode0
WoodScape: A multi-task, multi-camera fisheye dataset for autonomous drivingCode0
Multimodal Scale Consistency and Awareness for Monocular Self-Supervised Depth EstimationCode0
Hierarchical Potential-based Reward Shaping from Task SpecificationsCode0
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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