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 776800 of 6092 papers

TitleStatusHype
When Monte-Carlo Dropout Meets Multi-Exit: Optimizing Bayesian Neural Networks on FPGACode1
Multi-interactive Feature Learning and a Full-time Multi-modality Benchmark for Image Fusion and SegmentationCode1
UGainS: Uncertainty Guided Anomaly Instance SegmentationCode1
FusionAD: Multi-modality Fusion for Prediction and Planning Tasks of Autonomous DrivingCode1
Echoes Beyond Points: Unleashing the Power of Raw Radar Data in Multi-modality FusionCode1
OAFuser: Towards Omni-Aperture Fusion for Light Field Semantic SegmentationCode1
Car-Studio: Learning Car Radiance Fields from Single-View and Endless In-the-wild ImagesCode1
FDCT: Fast Depth Completion for Transparent ObjectsCode1
HVDetFusion: A Simple and Robust Camera-Radar Fusion FrameworkCode1
TwinLiteNet: An Efficient and Lightweight Model for Driveable Area and Lane Segmentation in Self-Driving CarsCode1
Asynchronous Blob Tracker for Event CamerasCode1
Explaining Autonomous Driving Actions with Visual Question AnsweringCode1
Domain Adaptation based Object Detection for Autonomous Driving in Foggy and Rainy WeatherCode1
HEAL-SWIN: A Vision Transformer On The SphereCode1
Linking vision and motion for self-supervised object-centric perceptionCode1
WaterScenes: A Multi-Task 4D Radar-Camera Fusion Dataset and Benchmarks for Autonomous Driving on Water SurfacesCode1
Towards Anytime Optical Flow Estimation with Event CamerasCode1
One-Versus-Others Attention: Scalable Multimodal Integration for Biomedical DataCode1
Parametric Depth Based Feature Representation Learning for Object Detection and Segmentation in Bird's Eye ViewCode1
Towards Building Self-Aware Object Detectors via Reliable Uncertainty Quantification and CalibrationCode1
Towards Safe Autonomous Driving Policies using a Neuro-Symbolic Deep Reinforcement Learning ApproachCode1
Intra- & Extra-Source Exemplar-Based Style Synthesis for Improved Domain GeneralizationCode1
PANet: LiDAR Panoptic Segmentation with Sparse Instance Proposal and AggregationCode1
SSC-RS: Elevate LiDAR Semantic Scene Completion with Representation Separation and BEV FusionCode1
Symphonize 3D Semantic Scene Completion with Contextual Instance QueriesCode1
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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