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 4051–4075 of 6092 papers

TitleStatusHype
CoPEM: Cooperative Perception Error Models for Autonomous Driving—0
5G PRS-Based Sensing: A Sensing Reference Signal Approach for Joint Sensing and Communication System—0
STGlow: A Flow-based Generative Framework with Dual Graphormer for Pedestrian Trajectory Prediction—0
PartCom: Part Composition Learning for 3D Open-Set Recognition—0
Rationale-aware Autonomous Driving Policy utilizing Safety Force Field implemented on CARLA Simulator—0
Perception-Based Sampled-Data Optimization of Dynamical Systems—0
Potential Auto-driving Threat: Universal Rain-removal Attack—0
A Tale of Two Cities: Data and Configuration Variances in Robust Deep Learning—0
Introduction and Exemplars of Uncertainty Decomposition—0
SelfOdom: Self-supervised Egomotion and Depth Learning via Bi-directional Coarse-to-Fine Scale Recovery—0
Monocular BEV Perception of Road Scenes via Front-to-Top View Projection—0
PAI3D: Painting Adaptive Instance-Prior for 3D Object Detection—0
NeurIPS 2022 Competition: Driving SMARTS—0
Self-Aligning Depth-regularized Radiance Fields for Asynchronous RGB-D Sequences—0
CXTrack: Improving 3D Point Cloud Tracking with Contextual Information—0
A Benchmark for Out of Distribution Detection in Point Cloud 3D Semantic Segmentation—0
RaLiBEV: Radar and LiDAR BEV Fusion Learning for Anchor Box Free Object Detection Systems—0
Multi-modal Fusion Technology based on Vehicle Information: A Survey—0
Deep Learning based Computer Vision Methods for Complex Traffic Environments Perception: A Review—0
Estimation of Appearance and Occupancy Information in Birds Eye View from Surround Monocular Images—0
Normalization Perturbation: A Simple Domain Generalization Method for Real-World Domain Shifts—0
RITA: Boost Driving Simulators with Realistic Interactive Traffic Flow—0
P4P: Conflict-Aware Motion Prediction for Planning in Autonomous Driving—0
An Empirical Bayes Analysis of Object Trajectory Representation ModelsCode0
Safe Real-World Autonomous Driving by Learning to Predict and Plan with a Mixture of Experts—0
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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