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 276–300 of 2605 papers

TitleStatusHype
Key Safety Design Overview in AI-driven Autonomous Vehicles—0
Enhancing 3D Object Detection in Autonomous Vehicles Based on Synthetic Virtual Environment Analysis—0
ITPNet: Towards Instantaneous Trajectory Prediction for Autonomous Driving—0
Bayesian Data Augmentation and Training for Perception DNN in Autonomous Aerial VehiclesCode0
A Real-Time Defense Against Object Vanishing Adversarial Patch Attacks for Object Detection in Autonomous Vehicles—0
doScenes: An Autonomous Driving Dataset with Natural Language Instruction for Human Interaction and Vision-Language NavigationCode0
GVDepth: Zero-Shot Monocular Depth Estimation for Ground Vehicles based on Probabilistic Cue Fusion—0
Segment-Level Road Obstacle Detection Using Visual Foundation Model Priors and Likelihood Ratios—0
VTD: Visual and Tactile Database for Driver State and Behavior Perception—0
Extrapolated Urban View Synthesis BenchmarkCode1
Stag-1: Towards Realistic 4D Driving Simulation with Video Generation ModelCode2
Text to Blind Motion—0
UNCOVER: Unknown Class Object Detection for Autonomous Vehicles in Real-time—0
Reinforcement Learning for Freeway Lane-Change Regulation via Connected Vehicles—0
LaserGuider: A Laser Based Physical Backdoor Attack against Deep Neural Networks—0
Distilling Diffusion Models to Efficient 3D LiDAR Scene CompletionCode2
On Privacy, Security, and Trustworthiness in Distributed Wireless Large AI Models (WLAM)—0
FoveaSPAD: Exploiting Depth Priors for Adaptive and Efficient Single-Photon 3D Imaging—0
ILASH: A Predictive Neural Architecture Search Framework for Multi-Task Applications—0
Generating Critical Scenarios for Testing Automated Driving Systems—0
Object Tracking in a 360^o View: A Novel Perspective on Bridging the Gap to Biomedical Advancements—0
Dynamic High-Order Control Barrier Functions with Diffuser for Safety-Critical Trajectory Planning at Signal-Free Intersections—0
Realistic Corner Case Generation for Autonomous Vehicles with Multimodal Large Language Model—0
A Multi-Loss Strategy for Vehicle Trajectory Prediction: Combining Off-Road, Diversity, and Directional Consistency LossesCode1
Machine Learning for Spectrum Sharing: A Survey—0
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Benchmark Results

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