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 2551–2600 of 6092 papers

TitleStatusHype
3D Data Augmentation for Driving Scenes on Camera—0
Driving Through Ghosts: Behavioral Cloning with False Positives—0
BiFF: Bi-level Future Fusion with Polyline-based Coordinate for Interactive Trajectory Prediction—0
DrivingStereo: A Large-Scale Dataset for Stereo Matching in Autonomous Driving Scenarios—0
BiCo-Fusion: Bidirectional Complementary LiDAR-Camera Fusion for Semantic- and Spatial-Aware 3D Object Detection—0
Driving Scene Perception Network: Real-time Joint Detection, Depth Estimation and Semantic Segmentation—0
Bias in AI-systems: A multi-step approach—0
Driving-RAG: Driving Scenarios Embedding, Search, and RAG Applications—0
Driving Policy Transfer via Modularity and Abstraction—0
Anchor Distance for 3D Multi-Object Distance Estimation from 2D Single Shot—0
Adapting to Length Shift: FlexiLength Network for Trajectory Prediction—0
Driving in the Occupancy World: Vision-Centric 4D Occupancy Forecasting and Planning via World Models for Autonomous Driving—0
Activation-wise Propagation: A Universal Strategy to Break Timestep Constraints in Spiking Neural Networks for 3D Data Processing—0
Driving in Real Life with Inverse Reinforcement Learning—0
Anchor-Based Spatio-Temporal Attention 3D Convolutional Networks for Dynamic 3D Point Cloud Sequences—0
Driving Everywhere with Large Language Model Policy Adaptation—0
Beyond Point Clouds: A Knowledge-Aided High Resolution Imaging Radar Deep Detector for Autonomous Driving—0
Driving Decision and Control for Autonomous Lane Change based on Deep Reinforcement Learning—0
Driving Datasets Literature Review—0
Beyond Patterns: Harnessing Causal Logic for Autonomous Driving Trajectory Prediction—0
Adapting Pre-trained 3D Models for Point Cloud Video Understanding via Cross-frame Spatio-temporal Perception—0
4D Millimeter-Wave Radar in Autonomous Driving: A Survey—0
Driving by the Rules: A Benchmark for Integrating Traffic Sign Regulations into Vectorized HD Map—0
Driving behavior recognition via self-discovery learning—0
DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving—0
DriveWorld: 4D Pre-trained Scene Understanding via World Models for Autonomous Driving—0
Beyond One Model Fits All: Ensemble Deep Learning for Autonomous Vehicles—0
Analyzing the Variety Loss in the Context of Probabilistic Trajectory Prediction—0
DriveVLM: The Convergence of Autonomous Driving and Large Vision-Language Models—0
DriveTrack: A Benchmark for Long-Range Point Tracking in Real-World Videos—0
Beyond Grand Theft Auto V for Training, Testing and Enhancing Deep Learning in Self Driving Cars—0
Analyzing Human Models that Adapt Online—0
DriveSceneGen: Generating Diverse and Realistic Driving Scenarios from Scratch—0
DriveScape: Towards High-Resolution Controllable Multi-View Driving Video Generation—0
Beyond Boundaries: A Comprehensive Survey of Transferable Attacks on AI Systems—0
DriveScape: High-Resolution Driving Video Generation by Multi-View Feature Fusion—0
DriveRX: A Vision-Language Reasoning Model for Cross-Task Autonomous Driving—0
Analyzing Computer Vision Data - The Good, the Bad and the Ugly—0
Driverseat: Crowdstrapping Learning Tasks for Autonomous Driving—0
DriverGym: Democratising Reinforcement Learning for Autonomous Driving—0
Driver Assistance System Based on Multimodal Data Hazard Detection—0
Analyzing and Mitigating Bias for Vulnerable Classes: Towards Balanced Representation in Dataset—0
Adaptable Deformable Convolutions for Semantic Segmentation of Fisheye Images in Autonomous Driving Systems—0
3D Can Be Explored In 2D: Pseudo-Label Generation for LiDAR Point Clouds Using Sensor-Intensity-Based 2D Semantic Segmentation—0
Driver2vec: Driver Identification from Automotive Data—0
Drive-R1: Bridging Reasoning and Planning in VLMs for Autonomous Driving with Reinforcement Learning—0
DriveMoE: Mixture-of-Experts for Vision-Language-Action Model in End-to-End Autonomous Driving—0
BEVSegFormer: Bird's Eye View Semantic Segmentation From Arbitrary Camera Rigs—0
Analyzing Accuracy Loss in Randomized Smoothing Defenses—0
DriveMind: A Dual-VLM based Reinforcement Learning Framework for Autonomous Driving—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