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 1751–1800 of 6092 papers

TitleStatusHype
DriveMoE: Mixture-of-Experts for Vision-Language-Action Model in End-to-End Autonomous Driving—0
Black-Box Adversarial Attack on Vision Language Models for Autonomous Driving—0
DUDES: Deep Uncertainty Distillation using Ensembles for Semantic Segmentation—0
DuEqNet: Dual-Equivariance Network in Outdoor 3D Object Detection for Autonomous Driving—0
BEVSegFormer: Bird's Eye View Semantic Segmentation From Arbitrary Camera Rigs—0
Analyzing Accuracy Loss in Randomized Smoothing Defenses—0
Analyze Drivers' Intervention Behavior During Autonomous Driving -- A VR-incorporated Approach—0
DriveMind: A Dual-VLM based Reinforcement Learning Framework for Autonomous Driving—0
BEV-SAN: Accurate BEV 3D Object Detection via Slice Attention Networks—0
AdaOcc: Adaptive-Resolution Occupancy Prediction—0
3DArticCyclists: Generating Synthetic Articulated 8D Pose-Controllable Cyclist Data for Computer Vision Applications—0
BEVPose: Unveiling Scene Semantics through Pose-Guided Multi-Modal BEV Alignment—0
BLOS-BEV: Navigation Map Enhanced Lane Segmentation Network, Beyond Line of Sight—0
Dynamically Local-Enhancement Planner for Large-Scale Autonomous Driving—0
An Efficient Generation Method based on Dynamic Curvature of the Reference Curve for Robust Trajectory Planning—0
Dynamic Compression Ratio Selection for Edge Inference Systems with Hard Deadlines—0
DriveGPT: Scaling Autoregressive Behavior Models for Driving—0
DriveGPT4-V2: Harnessing Large Language Model Capabilities for Enhanced Closed-Loop Autonomous Driving—0
BEV-MODNet: Monocular Camera based Bird's Eye View Moving Object Detection for Autonomous Driving—0
Dynamic Interaction-Aware Scene Understanding for Reinforcement Learning in Autonomous Driving—0
Dynamic Point Cloud Denoising via Gradient Fields—0
Dynamic Prioritization of Emergency Vehicles For Self-Organizing Traffic using VTL+EV *—0
Dynamic Scenario Representation Learning for Motion Forecasting with Heterogeneous Graph Convolutional Recurrent Networks—0
Dynamic Task Weighting Methods for Multi-task Networks in Autonomous Driving Systems—0
Analytical Safety Bounds for Trajectory Following Controllers in Autonomous Vehicles—0
DynOcc: Learning Single-View Depth from Dynamic Occlusion Cues—0
DynRsl-VLM: Enhancing Autonomous Driving Perception with Dynamic Resolution Vision-Language Models—0
DyRoNet: Dynamic Routing and Low-Rank Adapters for Autonomous Driving Streaming Perception—0
DySS: Dynamic Queries and State-Space Learning for Efficient 3D Object Detection from Multi-Camera Videos—0
DyTTP: Trajectory Prediction with Normalization-Free Transformers—0
EANet: Expert Attention Network for Online Trajectory Prediction—0
EAN-MapNet: Efficient Vectorized HD Map Construction with Anchor Neighborhoods—0
DriveGPT4: Interpretable End-to-end Autonomous Driving via Large Language Model—0
An Embarrassingly Pragmatic Introduction to Vision-based Autonomous Robots—0
Boosting the Transferability of Adversarial Samples via Attention—0
DriveGenVLM: Real-world Video Generation for Vision Language Model based Autonomous Driving—0
ECG-EmotionNet: Nested Mixture of Expert (NMoE) Adaptation of ECG-Foundation Model for Driver Emotion Recognition—0
DriveGen: Towards Infinite Diverse Traffic Scenarios with Large Models—0
Echo Planning for Autonomous Driving: From Current Observations to Future Trajectories and Back—0
Analysis of Truncated Singular Value Decomposition for Koopman Operator-Based Lane Change Model—0
Ada3Diff: Defending against 3D Adversarial Point Clouds via Adaptive Diffusion—0
DRIVE: Dual-Robustness via Information Variability and Entropic Consistency in Source-Free Unsupervised Domain Adaptation—0
Edge-Cloud Collaborative Computing on Distributed Intelligence and Model Optimization: A Survey—0
Edge-Cloud Collaborative Motion Planning for Autonomous Driving with Large Language Models—0
EdgeConv with Attention Module for Monocular Depth Estimation—0
Edge Detectors Can Make Deep Convolutional Neural Networks More Robust—0
Edge Device Deployment of Multi-Tasking Network for Self-Driving Operations—0
BOTT: Box Only Transformer Tracker for 3D Object Tracking—0
BEV-Locator: An End-to-end Visual Semantic Localization Network Using Multi-View Images—0
DriveDreamer4D: World Models Are Effective Data Machines for 4D Driving Scene Representation—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