SOTAVerified

Autonomous Vehicles

Autonomous vehicles is the task of making a vehicle that can guide itself 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: GSNet: Joint Vehicle Pose and Shape Reconstruction with Geometrical and Scene-aware Supervision )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 881–890 of 2605 papers

TitleStatusHype
Efficient Adversarial Input Generation via Neural Net Patching—0
Enhanced Multi-Target Tracking in Dynamic Environments: Distributed Flooding Control in the Random Finite Set Framework—0
Effects of Real-Life Traffic Sign Alteration on YOLOv7- an Object Recognition Model—0
Enhancement of High-definition Map Update Service Through Coverage-aware and Reinforcement Learning—0
Enhancing 3D Object Detection in Autonomous Vehicles Based on Synthetic Virtual Environment Analysis—0
Enhancing Autonomous Driving Safety through World Model-Based Predictive Navigation and Adaptive Learning Algorithms for 5G Wireless Applications—0
Effects of Controller Heterogeneity on Autonomous Vehicle Traffic—0
Enhancing High-Speed Cruising Performance of Autonomous Vehicles through Integrated Deep Reinforcement Learning Framework—0
Effects of Augmented-Reality-Based Assisting Interfaces on Drivers' Object-wise Situational Awareness in Highly Autonomous Vehicles—0
Bootstrapping confidence in future safety based on past safe operation—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1BAAMA3DP22.85—Unverified
2GSNetA3DP20.21—Unverified