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 2051–2100 of 6092 papers

TitleStatusHype
H-MBA: Hierarchical MamBa Adaptation for Multi-Modal Video Understanding in Autonomous Driving—0
NextStop: An Improved Tracker For Panoptic LIDAR Segmentation DataCode0
SenseRAG: Constructing Environmental Knowledge Bases with Proactive Querying for LLM-Based Autonomous Driving—0
Image Segmentation: Inducing graph-based learningCode0
Hybrid Machine Learning Model with a Constrained Action Space for Trajectory Prediction—0
LargeAD: Large-Scale Cross-Sensor Data Pretraining for Autonomous Driving—0
A Novel Vision Transformer for Camera-LiDAR Fusion based Traffic Object Segmentation—0
MObI: Multimodal Object Inpainting Using Diffusion Models—0
4D-CS: Exploiting Cluster Prior for 4D Spatio-Temporal LiDAR Semantic SegmentationCode0
LDMapNet-U: An End-to-End System for City-Scale Lane-Level Map Updating—0
GCP: Guarded Collaborative Perception with Spatial-Temporal Aware Malicious Agent DetectionCode0
Evaluating Scenario-based Decision-making for Interactive Autonomous Driving Using Rational Criteria: A Survey—0
Enhancing Large Vision Model in Street Scene Semantic Understanding through Leveraging Posterior Optimization Trajectory—0
Adverse Weather Conditions Augmentation of LiDAR Scenes with Latent Diffusion Models—0
MSC-Bench: Benchmarking and Analyzing Multi-Sensor Corruption for Driving Perception—0
GLane3D: Detecting Lanes with Graph of 3D Keypoints—0
EvOcc: Accurate Semantic Occupancy for Automated Driving Using Evidence Theory—0
PillarHist: A Quantization-aware Pillar Feature Encoder based on Height-aware Histogram—0
Enduring, Efficient and Robust Trajectory Prediction Attack in Autonomous Driving via Optimization-Driven Multi-Frame Perturbation Framework—0
S4-Driver: Scalable Self-Supervised Driving Multimodal Large Language Model with Spatio-Temporal Visual Representation—0
Adapting Pre-trained 3D Models for Point Cloud Video Understanding via Cross-frame Spatio-temporal Perception—0
DriveScape: High-Resolution Driving Video Generation by Multi-View Feature Fusion—0
DriveGPT4-V2: Harnessing Large Language Model Capabilities for Enhanced Closed-Loop Autonomous Driving—0
Track Any Anomalous Object:A Granular Video Anomaly Detection Pipeline—0
Toward Real-world BEV Perception: Depth Uncertainty Estimation via Gaussian Splatting—0
SDGOCC: Semantic and Depth-Guided Bird's-Eye View Transformation for 3D Multimodal Occupancy PredictionCode0
Distilling Monocular Foundation Model for Fine-grained Depth Completion—0
Balancing Two Classifiers via A Simplex ETF Structure for Model CalibrationCode0
DiffLO: Semantic-Aware LiDAR Odometry with Diffusion-Based Refinement—0
Leveraging Temporal Cues for Semi-Supervised Multi-View 3D Object Detection—0
VISTREAM: Improving Computation Efficiency of Visual Streaming Perception via Law-of-Charge-Conservation Inspired Spiking Neural Network—0
D^3CTTA: Domain-Dependent Decorrelation for Continual Test-Time Adaption of 3D LiDAR Segmentation—0
Cross-Modal 3D Representation with Multi-View Images and Point Clouds—0
Shape and Texture: What Influences Reliable Optical Flow Estimation?—0
CorrBEV: Multi-View 3D Object Detection by Correlation Learning with Multi-modal Prototypes—0
Leveraging SD Map to Augment HD Map-based Trajectory Prediction—0
JarvisIR: Elevating Autonomous Driving Perception with Intelligent Image Restoration—0
Communication Efficient Cooperative Edge AI via Event-Triggered Computation Offloading—0
Seeing is Not Believing: Adversarial Natural Object Optimization for Hard-Label 3D Scene Attacks—0
Multi-Modal Aerial-Ground Cross-View Place Recognition with Neural ODEs—0
DreamDrive: Generative 4D Scene Modeling from Street View Images—0
Toward Information Theoretic Active Inverse Reinforcement Learning—0
Automotive Speed Estimation: Sensor Types and Error Characteristics from OBD-II to ADASCode0
DecoratingFusion: A LiDAR-Camera Fusion Network with the Combination of Point-level and Feature-level Fusion—0
Research on vehicle detection based on improved YOLOv8 network—0
MR-Occ: Efficient Camera-LiDAR 3D Semantic Occupancy Prediction Using Hierarchical Multi-Resolution Voxel Representation—0
Multi-Modality Driven LoRA for Adverse Condition Depth Estimation—0
Leveraging Edge Intelligence and LLMs to Advance 6G-Enabled Internet of Automated Defense Vehicles—0
DepthMamba with Adaptive Fusion—0
Leveraging Large Language Models for Enhancing Autonomous Vehicle Perception—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