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 1776–1800 of 6092 papers

TitleStatusHype
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