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 211–220 of 2605 papers

TitleStatusHype
Toward a Low-Cost Perception System in Autonomous Vehicles: A Spectrum Learning Approach—0
MAGNNET: Multi-Agent Graph Neural Network-based Efficient Task Allocation for Autonomous Vehicles with Deep Reinforcement Learning—0
From Words to Collisions: LLM-Guided Evaluation and Adversarial Generation of Safety-Critical Driving ScenariosCode1
Mitigation of Camouflaged Adversarial Attacks in Autonomous Vehicles--A Case Study Using CARLA Simulator—0
Semantic Communication based on Generative AI: A New Approach to Image Compression and Edge Optimization—0
SpikingRTNH: Spiking Neural Network for 4D Radar Object Detection—0
ALBAR: Adversarial Learning approach to mitigate Biases in Action Recognition—0
An Optimal Cascade Feature-Level Spatiotemporal Fusion Strategy for Anomaly Detection in CAN Bus—0
Distributed Observer Design for Tracking Platoon of Connected and Autonomous Vehicles—0
DISC: Dataset for Analyzing Driving Styles In Simulated Crashes for Mixed Autonomy—0
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Benchmark Results

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