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

Showing 351375 of 2605 papers

TitleStatusHype
Categorical Depth Distribution Network for Monocular 3D Object DetectionCode1
Meta-RangeSeg: LiDAR Sequence Semantic Segmentation Using Multiple Feature AggregationCode1
Bootstrapping Autonomous Driving Radars with Self-Supervised LearningCode1
MODIPHY: Multimodal Obscured Detection for IoT using PHantom Convolution-Enabled Faster YOLOCode1
MotionLM: Multi-Agent Motion Forecasting as Language ModelingCode1
MSSPlace: Multi-Sensor Place Recognition with Visual and Text SemanticsCode1
Multi-Agent Routing Value Iteration NetworkCode1
Multi-Agent Trajectory Prediction With Heterogeneous Edge-Enhanced Graph Attention NetworkCode1
Multimodal Object Detection via Probabilistic EnsemblingCode1
Multimodal Virtual Point 3D DetectionCode1
Multi-Stream Cellular Test-Time Adaptation of Real-Time Models Evolving in Dynamic EnvironmentsCode1
MUSES: The Multi-Sensor Semantic Perception Dataset for Driving under UncertaintyCode1
Neural Network and ANFIS based auto-adaptive MPC for path tracking in autonomous vehiclesCode1
Neural Network Guided Evolutionary Fuzzing for Finding Traffic Violations of Autonomous VehiclesCode1
Monitoring and Adapting the Physical State of a Camera for Autonomous VehiclesCode1
NuPlan: A closed-loop ML-based planning benchmark for autonomous vehiclesCode1
CausalAgents: A Robustness Benchmark for Motion Forecasting using Causal RelationshipsCode1
On Data Fabrication in Collaborative Vehicular Perception: Attacks and CountermeasuresCode1
AVP-SLAM: Semantic Visual Mapping and Localization for Autonomous Vehicles in the Parking LotCode1
BAAM: Monocular 3D Pose and Shape Reconstruction With Bi-Contextual Attention Module and Attention-Guided ModelingCode1
CityRefer: Geography-aware 3D Visual Grounding Dataset on City-scale Point Cloud DataCode1
CoTV: Cooperative Control for Traffic Light Signals and Connected Autonomous Vehicles using Deep Reinforcement LearningCode1
Optimal Robust Network Design: Formulations and Algorithms for Maximizing Algebraic ConnectivityCode1
Efficient Reinforcement Learning via Decoupling Exploration and UtilizationCode1
Driving Style Representation in Convolutional Recurrent Neural Network Model of Driver IdentificationCode1
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Benchmark Results

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