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 1576–1600 of 6092 papers

TitleStatusHype
NRSeg: Noise-Resilient Learning for BEV Semantic Segmentation via Driving World ModelsCode0
Reinforcement learning with non-ergodic reward increments: robustness via ergodicity transformationsCode0
NUC-Net: Non-uniform Cylindrical Partition Network for Efficient LiDAR Semantic SegmentationCode0
NextStop: An Improved Tracker For Panoptic LIDAR Segmentation DataCode0
Active Data Acquisition in Autonomous Driving SimulationCode0
NiteDR: Nighttime Image De-Raining with Cross-View Sensor Cooperative Learning for Dynamic Driving ScenesCode0
NumbOD: A Spatial-Frequency Fusion Attack Against Object DetectorsCode0
DistFormer: Enhancing Local and Global Features for Monocular Per-Object Distance EstimationCode0
Neural Observation Field Guided Hybrid Optimization of Camera PlacementCode0
Neighbor-Vote: Improving Monocular 3D Object Detection through Neighbor Distance VotingCode0
Neural Enhanced Belief Propagation for Multiobject TrackingCode0
MWSIS: Multimodal Weakly Supervised Instance Segmentation with 2D Box Annotations for Autonomous DrivingCode0
Dirty Pixels: Towards End-to-End Image Processing and PerceptionCode0
MV-MOS: Multi-View Feature Fusion for 3D Moving Object SegmentationCode0
Beat the MTurkers: Automatic Image Labeling from Weak 3D SupervisionCode0
Multi-View 3D Object Detection Network for Autonomous DrivingCode0
Dimensionality of datasets in object detection networksCode0
An Active Learning Reliability Method for Systems with Partially Defined Performance FunctionsCode0
Neuro-Symbolic Evaluation of Text-to-Video Models using Formal VerificationCode0
Bench4Merge: A Comprehensive Benchmark for Merging in Realistic Dense Traffic with Micro-Interactive VehiclesCode0
nn-dependability-kit: Engineering Neural Networks for Safety-Critical Autonomous Driving SystemsCode0
DILLEMA: Diffusion and Large Language Models for Multi-Modal AugmentationCode0
No driver, No Regulation? --Online Legal Driving Behavior Monitoring for Self-driving VehiclesCode0
Multispectral Pedestrian Detection via Simultaneous Detection and SegmentationCode0
Balancing Two Classifiers via A Simplex ETF Structure for Model CalibrationCode0
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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