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 5326–5350 of 6092 papers

TitleStatusHype
SDOD:Real-time Segmenting and Detecting 3D Object by Depth—0
SDR-GAIN: A High Real-Time Occluded Pedestrian Pose Completion Method for Autonomous Driving—0
SDVRF: Sparse-to-Dense Voxel Region Fusion for Multi-modal 3D Object Detection—0
Searching for the Essence of Adversarial Perturbations—0
Searching Realistic-Looking Adversarial Objects For Autonomous Driving Systems—0
SECRM-2D: RL-Based Efficient and Comfortable Route-Following Autonomous Driving with Analytic Safety Guarantees—0
Secure Traffic Sign Recognition: An Attention-Enabled Universal Image Inpainting Mechanism against Light Patch Attacks—0
Secure Vehicle Communications Using Proof-of-Nonce Blockchain—0
Security and Privacy Challenges in Deep Learning Models—0
Seeing Beyond Views: Multi-View Driving Scene Video Generation with Holistic Attention—0
Seeing in the dark with recurrent convolutional neural networks—0
Seeing is Not Believing: Adversarial Natural Object Optimization for Hard-Label 3D Scene Attacks—0
Seeking to Collide: Online Safety-Critical Scenario Generation for Autonomous Driving with Retrieval Augmented Large Language Models—0
SEFormer: Structure Embedding Transformer for 3D Object Detection—0
Segment Anything, Even Occluded—0
Segment-Fusion: Hierarchical Context Fusion for Robust 3D Semantic Segmentation—0
Segment, Lift and Fit: Automatic 3D Shape Labeling from 2D Prompts—0
SegVoxelNet: Exploring Semantic Context and Depth-aware Features for 3D Vehicle Detection from Point Cloud—0
Selective Communication for Cooperative Perception in End-to-End Autonomous Driving—0
Selective Focus: Investigating Semantics Sensitivity in Post-training Quantization for Lane Detection—0
Selective Sensor Fusion for Neural Visual-Inertial Odometry—0
Self-Awareness Safety of Deep Reinforcement Learning in Road Traffic Junction Driving—0
Self-Aware Trajectory Prediction for Safe Autonomous Driving—0
Self-Configurable Stabilized Real-Time Detection Learning for Autonomous Driving Applications—0
Self-Driving Car Racing: Application of Deep Reinforcement Learning—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