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 2401–2425 of 2605 papers

TitleStatusHype
One Thousand and One Hours: Self-driving Motion Prediction DatasetCode0
FormulaZero: Distributionally Robust Online Adaptation via Offline Population SynthesisCode0
Utilizing Neural Networks for Semantic Segmentation on RGB/LiDAR Fused Data for Off-road Autonomous Military Vehicle PerceptionCode0
Accuracy-Efficiency Trade-Offs and Accountability in Distributed ML SystemsCode0
AttDLNet: Attention-based DL Network for 3D LiDAR Place RecognitionCode0
Agent-aware State Estimation in Autonomous VehiclesCode0
Reinforcement LearningCode0
Edge-Enabled Collaborative Object Detection for Real-Time Multi-Vehicle PerceptionCode0
Two is Better Than One: Digital Siblings to Improve Autonomous Driving TestingCode0
LiMTR: Time Series Motion Prediction for Diverse Road Users through Multimodal Feature IntegrationCode0
Verifiable Goal Recognition for Autonomous Driving with OcclusionsCode0
Towards Safety Verification of Direct Perception Neural NetworksCode0
Formal Security Analysis of Neural Networks using Symbolic IntervalsCode0
Verifiable Obstacle DetectionCode0
Fool the Stoplight: Realistic Adversarial Patch Attacks on Traffic Light DetectorsCode0
Visual Exploration and Energy-aware Path Planning via Reinforcement LearningCode0
On the Importance of Stereo for Accurate Depth Estimation: An Efficient Semi-Supervised Deep Neural Network ApproachCode0
ecg2o: A Seamless Extension of g2o for Equality-Constrained Factor Graph OptimizationCode0
FollowMe: Vehicle Behaviour Prediction in Autonomous Vehicle SettingsCode0
Compressing Sensor Data for Remote Assistance of Autonomous Vehicles using Deep Generative ModelsCode0
ReMAV: Reward Modeling of Autonomous Vehicles for Finding Likely Failure EventsCode0
Semantic Segmentation for Autonomous Driving: Model Evaluation, Dataset Generation, Perspective Comparison, and Real-Time CapabilityCode0
Semantic Segmentation with High Inference Speed in Off-Road EnvironmentsCode0
DynaSLAM: Tracking, Mapping and Inpainting in Dynamic ScenesCode0
Camera-Only 3D Panoptic Scene Completion for Autonomous Driving through Differentiable Object ShapesCode0
Show:102550
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Benchmark Results

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