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 2176–2200 of 6092 papers

TitleStatusHype
Vehicle Behavior Prediction by Episodic-Memory Implanted NDTCode0
Inherent Diverse Redundant Safety Mechanisms for AI-based Software Elements in Automotive Applications—0
AYDIV: Adaptable Yielding 3D Object Detection via Integrated Contextual Vision TransformerCode1
Towards Explainable, Safe Autonomous Driving with Language Embeddings for Novelty Identification and Active Learning: Framework and Experimental Analysis with Real-World Data Sets—0
Neural Rendering based Urban Scene Reconstruction for Autonomous Driving—0
Diffusion-ES: Gradient-free Planning with Diffusion for Autonomous Driving and Zero-Shot Instruction FollowingCode2
CurveFormer++: 3D Lane Detection by Curve Propagation with Temporal Curve Queries and Attention—0
Enhancement of High-definition Map Update Service Through Coverage-aware and Reinforcement Learning—0
Explainable AI for Safe and Trustworthy Autonomous Driving: A Systematic Review—0
Editable Scene Simulation for Autonomous Driving via Collaborative LLM-AgentsCode3
Optimizing Delegation in Collaborative Human-AI Hybrid Teams—0
Driving Everywhere with Large Language Model Policy Adaptation—0
Compressing Deep Reinforcement Learning Networks with a Dynamic Structured Pruning Method for Autonomous Driving—0
BioDrone: A Bionic Drone-based Single Object Tracking Benchmark for Robust Vision—0
Tuning the feedback controller gains is a simple way to improve autonomous driving performance—0
OASim: an Open and Adaptive Simulator based on Neural Rendering for Autonomous DrivingCode3
Controllable Diverse Sampling for Diffusion Based Motion Behavior Forecasting—0
Informed Reinforcement Learning for Situation-Aware Traffic Rule ExceptionsCode0
Efficient and Interpretable Traffic Destination Prediction using Explainable Boosting MachinesCode0
Improving Robustness of LiDAR-Camera Fusion Model against Weather Corruption from Fusion Strategy Perspective—0
SIMPL: A Simple and Efficient Multi-agent Motion Prediction Baseline for Autonomous DrivingCode3
Hybrid-Prediction Integrated Planning for Autonomous Driving—0
Evaluating the Robustness of Off-Road Autonomous Driving Segmentation against Adversarial Attacks: A Dataset-Centric analysisCode0
Multimodal-Enhanced Objectness Learner for Corner Case Detection in Autonomous DrivingCode1
RIDERS: Radar-Infrared Depth Estimation for Robust SensingCode1
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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