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 3201–3225 of 6092 papers

TitleStatusHype
Lane Graph as Path: Continuity-preserving Path-wise Modeling for Online Lane Graph ConstructionCode1
Modeling Continuous Motion for 3D Point Cloud Object Tracking—0
V2V4Real: A Real-world Large-scale Dataset for Vehicle-to-Vehicle Cooperative PerceptionCode2
A Simple Baseline for Supervised Surround-view Depth Estimation—0
A Generalized Multi-Modal Fusion Detection Framework—0
FusionLoc: Camera-2D LiDAR Fusion Using Multi-Head Self-Attention for End-to-End Serving Robot Relocalization—0
Sequential Spatial Network for Collision Avoidance in Autonomous Driving—0
BCSSN: Bi-direction Compact Spatial Separable Network for Collision Avoidance in Autonomous Driving—0
Traj-MAE: Masked Autoencoders for Trajectory Prediction—0
SPOTR: Spatio-temporal Pose Transformers for Human Motion Prediction—0
Lossless Point Cloud Geometry and Attribute Compression Using a Learned Conditional Probability ModelCode1
Learning Feasibility Constraints for Control Barrier Functions—0
SemARFlow: Injecting Semantics into Unsupervised Optical Flow Estimation for Autonomous DrivingCode1
HumanBench: Towards General Human-centric Perception with Projector Assisted PretrainingCode2
Lifelong-MonoDepth: Lifelong Learning for Multi-Domain Monocular Metric Depth EstimationCode1
Rethinking Range View Representation for LiDAR Segmentation—0
RMMDet: Road-Side Multitype and Multigroup Sensor Detection System for Autonomous DrivingCode1
MBPTrack: Improving 3D Point Cloud Tracking with Memory Networks and Box Priors—0
Learning Representation for Anomaly Detection of Vehicle Trajectories—0
Exploring Adversarial Attacks on Neural Networks: An Explainable ApproachCode0
You Only Crash Once: Improved Object Detection for Real-Time, Sim-to-Real Hazardous Terrain Detection and Classification for Autonomous Planetary Landings—0
A Threefold Review on Deep Semantic Segmentation: Efficiency-oriented, Temporal and Depth-aware design—0
Dynamic Scenario Representation Learning for Motion Forecasting with Heterogeneous Graph Convolutional Recurrent Networks—0
Deep Occupancy-Predictive Representations for Autonomous Driving—0
OpenOccupancy: A Large Scale Benchmark for Surrounding Semantic Occupancy PerceptionCode2
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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