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

Showing 801825 of 6092 papers

TitleStatusHype
DVIS: Decoupled Video Instance Segmentation FrameworkCode1
Dynamic Environment Prediction in Urban Scenes using Recurrent Representation LearningCode1
Dur360BEV: A Real-world 360-degree Single Camera Dataset and Benchmark for Bird-Eye View Mapping in Autonomous DrivingCode1
Dual Radar: A Multi-modal Dataset with Dual 4D Radar for Autonomous DrivingCode1
DualAD: Dual-Layer Planning for Reasoning in Autonomous DrivingCode1
IPDAE: Improved Patch-Based Deep Autoencoder for Lossy Point Cloud Geometry CompressionCode1
Benchmarking Robustness of 3D Object Detection to Common CorruptionsCode1
Benchmarking the Robustness of LiDAR-Camera Fusion for 3D Object DetectionCode1
DSTIGCN: Deformable Spatial-Temporal Interaction Graph Convolution Network for Pedestrian Trajectory PredictionCode1
DualDiff: Dual-branch Diffusion Model for Autonomous Driving with Semantic FusionCode1
JM3D & JM3D-LLM: Elevating 3D Understanding with Joint Multi-modal CuesCode1
DUSA: Decoupled Unsupervised Sim2Real Adaptation for Vehicle-to-Everything Collaborative PerceptionCode1
A Multi-Loss Strategy for Vehicle Trajectory Prediction: Combining Off-Road, Diversity, and Directional Consistency LossesCode1
BetaZero: Belief-State Planning for Long-Horizon POMDPs using Learned ApproximationsCode1
EC-Depth: Exploring the consistency of self-supervised monocular depth estimation in challenging scenesCode1
360 Depth Estimation in the Wild -- The Depth360 Dataset and the SegFuse NetworkCode1
Keypoints-Based Deep Feature Fusion for Cooperative Vehicle Detection of Autonomous DrivingCode1
Key Points Estimation and Point Instance Segmentation Approach for Lane DetectionCode1
Efficient Object Detection in Autonomous Driving using Spiking Neural Networks: Performance, Energy Consumption Analysis, and Insights into Open-set Object DiscoveryCode1
Homography Loss for Monocular 3D Object DetectionCode1
Driving Style Alignment for LLM-powered Driver AgentCode1
AFDet: Anchor Free One Stage 3D Object DetectionCode1
LAformer: Trajectory Prediction for Autonomous Driving with Lane-Aware Scene ConstraintsCode1
BEVDiffLoc: End-to-End LiDAR Global Localization in BEV View based on Diffusion ModelCode1
DriveTester: A Unified Platform for Simulation-Based Autonomous Driving TestingCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ReasonNetDriving Score79.95Unverified
2InterFuserDriving Score76.18Unverified
3TCPDriving Score75.14Unverified
4TF++ WPDriving Score66.32Unverified
5Learning From All Vehicles (LAV)Driving Score61.85Unverified
6TransFuserDriving Score61.18Unverified
7TransFuser (Reproduced)Driving Score55.04Unverified
8TCP (Reproduced)Driving Score47.91Unverified
9Latent TransFuserDriving Score45.2Unverified
10GRIADDriving Score36.79Unverified
#ModelMetricClaimedVerifiedStatus
1Geometric FusionRC69.17Unverified
2TransFuserRC56.36Unverified
#ModelMetricClaimedVerifiedStatus
1Geometric FusionRC86.91Unverified
2TransFuserRC78.41Unverified