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 4226–4250 of 6092 papers

TitleStatusHype
How Private Is Your RL Policy? An Inverse RL Based Analysis FrameworkCode0
Self-Ensemling for 3D Point Cloud Domain Adaption—0
Real-time Collision Risk Estimation based on Stochastic Reachability SpacesCode0
FPPN: Future Pseudo-LiDAR Frame Prediction for Autonomous Driving—0
Radar Occupancy Prediction with Lidar Supervision while Preserving Long-Range Sensing and Penetrating Capabilities—0
Causal Imitative Model for Autonomous DrivingCode1
MDPFuzz: Testing Models Solving Markov Decision Processes—0
3D Hierarchical Refinement and Augmentation for Unsupervised Learning of Depth and Pose from Monocular Video—0
SSAGCN: Social Soft Attention Graph Convolution Network for Pedestrian Trajectory Prediction—0
SGM3D: Stereo Guided Monocular 3D Object DetectionCode1
On Salience-Sensitive Sign Classification in Autonomous Vehicle Path Planning: Experimental Explorations with a Novel Dataset—0
Probabilistic Approach for Road-Users Detection—0
Personalized Federated Learning of Driver Prediction Models for Autonomous Driving—0
The Norm Must Go On: Dynamic Unsupervised Domain Adaptation by NormalizationCode1
SaDe: Learning Models that Provably Satisfy Domain Constraints—0
Scalable Primitives for Generalized Sensor Fusion in Autonomous Vehicles—0
Gradient-Free Adversarial Training Against Image Corruption for Learning-based Steering—0
Adversarially Robust 3D Point Cloud Recognition Using Self-Supervisions—0
Pattern-Aware Data Augmentation for LiDAR 3D Object Detection—0
Large-Scale Video Analytics through Object-Level Consolidation—0
ConDA: Unsupervised Domain Adaptation for LiDAR Segmentation via Regularized Domain ConcatenationCode0
NeeDrop: Self-supervised Shape Representation from Sparse Point Clouds using Needle DroppingCode1
MultiPath++: Efficient Information Fusion and Trajectory Aggregation for Behavior PredictionCode1
Towards Autonomous Driving of Personal Mobility with Small and Noisy Dataset using Tsallis-statistics-based Behavioral Cloning—0
Anomaly-Aware Semantic Segmentation by Leveraging Synthetic-Unknown Data—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