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 2276–2300 of 2605 papers

TitleStatusHype
Causal Scene BERT: Improving object detection by searching for challenging groups of data—0
CC-SGG: Corner Case Scenario Generation using Learned Scene Graphs—0
Censored Deep Reinforcement Patrolling with Information Criterion for Monitoring Large Water Resources using Autonomous Surface Vehicles—0
Center Feature Fusion: Selective Multi-Sensor Fusion of Center-based Objects—0
CenterLineDet: CenterLine Graph Detection for Road Lanes with Vehicle-mounted Sensors by Transformer for HD Map Generation—0
GraphSCENE: On-Demand Critical Scenario Generation for Autonomous Vehicles in Simulation—0
Certified Interpretability Robustness for Class Activation Mapping—0
CFTrack: Center-based Radar and Camera Fusion for 3D Multi-Object Tracking—0
CGAP2: Context and gap aware predictive pose framework for early detection of gestures—0
Challenges and Obstacles Towards Deploying Deep Learning Models on Mobile Devices—0
Challenges of YOLO Series for Object Detection in Extremely Heavy Rain: CALRA Simulator based Synthetic Evaluation Dataset—0
Channel-Aware Throughput Maximization for Cooperative Data Fusion in CAV—0
Channel Boosting Feature Ensemble for Radar-based Object Detection—0
Characterization and Mitigation of Insufficiencies in Automated Driving Systems—0
Characterizing Soft-Error Resiliency in Arm's Ethos-U55 Embedded Machine Learning Accelerator—0
CheckINN: Wide Range Neural Network Verification in Imandra (Extended)—0
ChipNet: Real-Time LiDAR Processing for Drivable Region Segmentation on an FPGA—0
CIMRL: Combining IMitation and Reinforcement Learning for Safe Autonomous Driving—0
CityX: Controllable Procedural Content Generation for Unbounded 3D Cities—0
Classical and Quantum Physical Reservoir Computing for Onboard Artificial Intelligence Systems: A Perspective—0
Classification of Safety Driver Attention During Autonomous Vehicle Operation—0
Physical Backdoor Attacks to Lane Detection Systems in Autonomous Driving—0
CLIP-RLDrive: Human-Aligned Autonomous Driving via CLIP-Based Reward Shaping in Reinforcement Learning—0
Closing the gap towards end-to-end autonomous vehicle system—0
Cloud2Edge Elastic AI Framework for Prototyping and Deployment of AI Inference Engines in Autonomous Vehicles—0
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Benchmark Results

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