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 2851–2875 of 6092 papers

TitleStatusHype
IROAM: Improving Roadside Monocular 3D Object Detection Learning from Autonomous Vehicle Data Domain—0
Is a 3D-Tokenized LLM the Key to Reliable Autonomous Driving?—0
TrISec: Training Data-Unaware Imperceptible Security Attacks on Deep Neural Networks—0
Is Behavior Cloning All You Need? Understanding Horizon in Imitation Learning—0
Developing Driving Strategies Efficiently: A Skill-Based Hierarchical Reinforcement Learning Approach—0
Hierarchical Instance Mixing across Domains in Aerial Segmentation—0
ISETAuto: Detecting vehicles with depth and radiance information—0
A Theoretical-Empirical Approach to Estimating Sample Complexity of DNNs—0
Is it Safe to Drive? An Overview of Factors, Challenges, and Datasets for Driveability Assessment in Autonomous Driving—0
Is Neuron Coverage Needed to Make Person Detection More Robust?—0
Hierarchical Insights: Exploiting Structural Similarities for Reliable 3D Semantic Segmentation—0
A Fast Integrated Planning and Control Framework for Autonomous Driving via Imitation Learning—0
Is Your HD Map Constructor Reliable under Sensor Corruptions?—0
Iterative Deep Compression : Compressing Deep Networks for Classification and Semantic Segmentation—0
LDMapNet-U: An End-to-End System for City-Scale Lane-Level Map Updating—0
Ithaca365: Dataset and Driving Perception under Repeated and Challenging Weather Conditions—0
Hierarchical Game-Theoretic Planning for Autonomous Vehicles—0
It's All Around You: Range-Guided Cylindrical Network for 3D Object Detection—0
Adversarial Rain Attack and Defensive Deraining for DNN Perception—0
JarvisIR: Elevating Autonomous Driving Perception with Intelligent Image Restoration—0
Hierarchical End-to-End Autonomous Driving: Integrating BEV Perception with Deep Reinforcement Learning—0
JFP: Joint Future Prediction with Interactive Multi-Agent Modeling for Autonomous Driving—0
JiSAM: Alleviate Labeling Burden and Corner Case Problems in Autonomous Driving via Minimal Real-World Data—0
Cross-Modality Program Representation Learning for Electronic Design Automation with High-Level Synthesis—0
Cross-Modality Domain Adaptation for Freespace Detection: A Simple yet Effective Baseline—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