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 3201–3250 of 6092 papers

TitleStatusHype
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
Self-driving scale car trained by Deep reinforcement learning—0
Self-Ensemling for 3D Point Cloud Domain Adaption—0
Self-Interpretable Time Series Prediction with Counterfactual Explanations—0
Self-supervised classification of dynamic obstacles using the temporal information provided by videos—0
Self-supervised Depth Estimation Leveraging Global Perception and Geometric Smoothness Using On-board Videos—0
Self-Supervised Domain Mismatch Estimation for Autonomous Perception—0
SelfOdom: Self-supervised Egomotion and Depth Learning via Bi-directional Coarse-to-Fine Scale Recovery—0
Self-Supervised Image-to-Point Distillation via Semantically Tolerant Contrastive Loss—0
Self-supervised learning for autonomous vehicles perception: A conciliation between analytical and learning methods—0
Self-supervised Learning for Pre-Training 3D Point Clouds: A Survey—0
Self-Supervised Multi-Frame Neural Scene Flow—0
Self-Supervised Multi-Object Tracking For Autonomous Driving From Consistency Across Timescales—0
Self-Supervised Pre-training with Combined Datasets for 3D Perception in Autonomous Driving—0
Self-Supervised Simultaneous Multi-Step Prediction of Road Dynamics and Cost Map—0
Self Training Autonomous Driving Agent—0
SELMA: SEmantic Large-scale Multimodal Acquisitions in Variable Weather, Daytime and Viewpoints—0
Evaluating Robustness to Context-Sensitive Feature Perturbations of Different Granularities—0
Semantically Adversarial Scenario Generation with Explicit Knowledge Guidance—0
Semantic and Feature Guided Uncertainty Quantification of Visual Localization for Autonomous Vehicles—0
SemanticBEVFusion: Rethink LiDAR-Camera Fusion in Unified Bird's-Eye View Representation for 3D Object Detection—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