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 1051–1100 of 6092 papers

TitleStatusHype
M3D: Dual-Stream Selective State Spaces and Depth-Driven Framework for High-Fidelity Single-View 3D ReconstructionCode0
Robust 3D Semantic Occupancy Prediction with Calibration-free Spatial TransformationCode1
Calibrated and Efficient Sampling-Free Confidence Estimation for LiDAR Scene Semantic Segmentation—0
DeSiRe-GS: 4D Street Gaussians for Static-Dynamic Decomposition and Surface Reconstruction for Urban Driving ScenesCode3
The ADUULM-360 Dataset -- A Multi-Modal Dataset for Depth Estimation in Adverse WeatherCode0
DrivingSphere: Building a High-fidelity 4D World for Closed-loop SimulationCode2
MGNiceNet: Unified Monocular Geometric Scene UnderstandingCode0
SignEye: Traffic Sign Interpretation from Vehicle First-Person View—0
ModeSeq: Taming Sparse Multimodal Motion Prediction with Sequential Mode Modeling—0
Unveiling the Hidden: Online Vectorized HD Map Construction with Clip-Level Token Interaction and Propagation—0
V2X-Radar: A Multi-modal Dataset with 4D Radar for Cooperative Perception—0
MTA: Multimodal Task Alignment for BEV Perception and Captioning—0
Automatic Discovery and Assessment of Interpretable Systematic Errors in Semantic Segmentation—0
Attention-based U-Net Method for Autonomous Lane Detection—0
Prompt-Guided Environmentally Consistent Adversarial Patch—0
Guided Learning: Lubricating End-to-End Modeling for Multi-stage Decision-making—0
Advancing Autonomous Driving Perception: Analysis of Sensor Fusion and Computer Vision Techniques—0
Explanation for Trajectory Planning using Multi-modal Large Language Model for Autonomous Driving—0
Imagine-2-Drive: Leveraging High-Fidelity World Models via Multi-Modal Diffusion Policies—0
Methodology for a Statistical Analysis of Influencing Factors on 3D Object Detection Performance—0
3D Multi-Object Tracking with Semi-Supervised GRU-Kalman Filter—0
Imitation Learning from Observations: An Autoregressive Mixture of Experts Approach—0
ALOcc: Adaptive Lifting-based 3D Semantic Occupancy and Cost Volume-based Flow PredictionCode1
OWLed: Outlier-weighed Layerwise Pruning for Efficient Autonomous Driving FrameworkCode0
Model Partition and Resource Allocation for Split Learning in Vehicular Edge Networks—0
SIESEF-FusionNet: Spatial Inter-correlation Enhancement and Spatially-Embedded Feature Fusion Network for LiDAR Point Cloud Semantic Segmentation—0
Large-scale moral machine experiment on large language modelsCode1
LSSInst: Improving Geometric Modeling in LSS-Based BEV Perception with Instance RepresentationCode1
Integrating Object Detection Modality into Visual Language Model for Enhanced Autonomous Driving Agent—0
ZOPP: A Framework of Zero-shot Offboard Panoptic Perception for Autonomous Driving—0
SimpleBEV: Improved LiDAR-Camera Fusion Architecture for 3D Object Detection—0
Expectation vs. Reality: Towards Verification of Psychological Games—0
Open-set object detection: towards unified problem formulation and benchmarking—0
Few-Shot Task Learning through Inverse Generative Modeling—0
IGDrivSim: A Benchmark for the Imitation Gap in Autonomous DrivingCode1
LidaRefer: Outdoor 3D Visual Grounding for Autonomous Driving with Transformers—0
Federated Data-Driven Kalman Filtering for State Estimation—0
Graph-Based Multi-Modal Sensor Fusion for Autonomous Driving—0
Hybrid Attention for Robust RGB-T Pedestrian Detection in Real-World Conditions—0
OccLoff: Learning Optimized Feature Fusion for 3D Occupancy Prediction—0
Towards 3D Semantic Scene Completion for Autonomous Driving: A Meta-Learning Framework Empowered by Deformable Large-Kernel Attention and Mamba Model—0
Knowledge Graphs of Driving Scenes to Empower the Emerging Capabilities of Neurosymbolic AICode0
Multi-modal NeRF Self-Supervision for LiDAR Semantic Segmentation—0
Exploring the Interplay Between Video Generation and World Models in Autonomous Driving: A Survey—0
Precise Drive with VLM: First Prize Solution for PRCV 2024 Drive LM challenge—0
Region-Guided Attack on the Segment Anything Model (SAM)—0
Traffic and Safety Rule Compliance of Humans in Diverse Driving Situations—0
Learning Multiple Initial Solutions to Optimization ProblemsCode1
Polar R-CNN: End-to-End Lane Detection with Fewer AnchorsCode1
ROAD-Waymo: Action Awareness at Scale for Autonomous DrivingCode1
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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