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 2551–2575 of 6092 papers

TitleStatusHype
Panoptic Perception for Autonomous Driving: A Survey—0
Adversarial Manhole: Challenging Monocular Depth Estimation and Semantic Segmentation Models with Patch AttackCode0
EMDFNet: Efficient Multi-scale and Diverse Feature Network for Traffic Sign Detection—0
Driving in the Occupancy World: Vision-Centric 4D Occupancy Forecasting and Planning via World Models for Autonomous Driving—0
FusionSAM: Latent Space driven Segment Anything Model for Multimodal Fusion and Segmentation—0
Bridging the Gap between Real-world and Synthetic Images for Testing Autonomous Driving Systems—0
CV-MOS: A Cross-View Model for Motion SegmentationCode0
Making Large Language Models Better Planners with Reasoning-Decision Alignment—0
TraIL-Det: Transformation-Invariant Local Feature Networks for 3D LiDAR Object Detection with Unsupervised Pre-Training—0
Exploring Reliable Matching with Phase Enhancement for Night-time Semantic Segmentation—0
AdaOcc: Adaptive-Resolution Occupancy Prediction—0
CSS-Segment: 2nd Place Report of LSVOS Challenge VOS Track—0
General Intelligent Imaging and Uncertainty Quantification by Deterministic Diffusion Model—0
A Safe Self-evolution Algorithm for Autonomous Driving Based on Data-Driven Risk Quantification Model—0
Enhancing Sampling Protocol for Point Cloud Classification Against Corruptions—0
Revisiting Cross-Domain Problem for LiDAR-based 3D Object Detection—0
Can LLMs Understand Social Norms in Autonomous Driving Games?—0
Multimodal Foundational Models for Unsupervised 3D General Obstacle Detection—0
A Safe and Efficient Self-evolving Algorithm for Decision-making and Control of Autonomous Driving Systems—0
Pareto Inverse Reinforcement Learning for Diverse Expert Policy Generation—0
MambaOcc: Visual State Space Model for BEV-based Occupancy Prediction with Local Adaptive ReorderingCode0
Privacy-preserving Universal Adversarial Defense for Black-box Models—0
Open 3D World in Autonomous Driving—0
MV-MOS: Multi-View Feature Fusion for 3D Moving Object SegmentationCode0
Edge-Cloud Collaborative Motion Planning for Autonomous Driving with Large Language Models—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