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

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Showing 5301–5350 of 6092 papers

TitleStatusHype
Scalable Adversarial Attack on Graph Neural Networks with Alternating Direction Method of Multipliers—0
Scalable Autonomous Vehicle Safety Validation through Dynamic Programming and Scene Decomposition—0
Scalable Decentralized Cooperative Platoon using Multi-Agent Deep Reinforcement Learning—0
Scalable Detection and Tracking of Geometric Extended Objects—0
Scalable Place Recognition Under Appearance Change for Autonomous Driving—0
Scalable Primitives for Generalized Sensor Fusion in Autonomous Vehicles—0
Scaling Is All You Need: Autonomous Driving with JAX-Accelerated Reinforcement Learning—0
Scaling Motion Forecasting Models with Ensemble Distillation—0
SCaRL- A Synthetic Multi-Modal Dataset for Autonomous Driving—0
Sce2DriveX: A Generalized MLLM Framework for Scene-to-Drive Learning—0
Scenario-Transferable Semantic Graph Reasoning for Interaction-Aware Probabilistic Prediction—0
Scenario Understanding of Traffic Scenes Through Large Visual Language Models—0
Scene-Aware Conversational ADAS with Generative AI for Real-Time Driver Assistance—0
SceneCalib: Automatic Targetless Calibration of Cameras and Lidars in Autonomous Driving—0
Neural Eulerian Scene Flow Fields—0
SceneLLM: Implicit Language Reasoning in LLM for Dynamic Scene Graph Generation—0
Efficient Data Representation for Motion Forecasting: A Scene-Specific Trajectory Set Approach—0
Scene Transformer: A unified architecture for predicting future trajectories of multiple agents—0
Scene Understanding for Autonomous Driving—0
Scene Understanding Networks for Autonomous Driving based on Around View Monitoring System—0
S&CNet: Monocular Depth Completion for Autonomous Systems and 3D Reconstruction—0
SCP: Scene Completion Pre-training for 3D Object Detection—0
SCR-Graph: Spatial-Causal Relationships based Graph Reasoning Network for Human Action Prediction—0
SD++: Enhancing Standard Definition Maps by Incorporating Road Knowledge using LLMs—0
SDGE: Stereo Guided Depth Estimation for 360^ Camera Sets—0
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