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

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Showing 781–790 of 2605 papers

TitleStatusHype
A Parameter Adaptive Trajectory Tracking and Motion Control Framework for Autonomous Vehicle—0
CatFree3D: Category-agnostic 3D Object Detection with Diffusion—0
Categorical Traffic Transformer: Interpretable and Diverse Behavior Prediction with Tokenized Latent—0
CAT: Closed-loop Adversarial Training for Safe End-to-End Driving—0
AOP-Net: All-in-One Perception Network for Joint LiDAR-based 3D Object Detection and Panoptic Segmentation—0
Adversarial Examples: Opportunities and Challenges—0
A Computer Vision Approach for Autonomous Cars to Drive Safe at Construction Zone—0
4C: A Computation, Communication, and Control Co-Design Framework for CAVs—0
LD-Scene: LLM-Guided Diffusion for Controllable Generation of Adversarial Safety-Critical Driving Scenarios—0
CARMA: Context-Aware Runtime Reconfiguration for Energy-Efficient Sensor Fusion—0
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Benchmark Results

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