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
COOPERNAUT: End-to-End Driving with Cooperative Perception for Networked VehiclesCode1
Fast nonlinear risk assessment for autonomous vehicles using learned conditional probabilistic models of agent futuresCode1
Memory-augmented Online Video Anomaly DetectionCode1
Federated Deep Reinforcement Learning for the Distributed Control of NextG Wireless NetworksCode1
Finding Failures in High-Fidelity Simulation using Adaptive Stress Testing and the Backward AlgorithmCode1
FisheyeDepth: A Real Scale Self-Supervised Depth Estimation Model for Fisheye CameraCode1
RGB-X Object Detection via Scene-Specific Fusion ModulesCode1
Fine-Grained Pillar Feature Encoding Via Spatio-Temporal Virtual Grid for 3D Object DetectionCode1
BAT: Behavior-Aware Human-Like Trajectory Prediction for Autonomous DrivingCode1
Beyond the Field-of-View: Enhancing Scene Visibility and Perception with Clip-Recurrent TransformerCode1
FollowNet: A Comprehensive Benchmark for Car-Following Behavior ModelingCode1
From Shadows to Safety: Occlusion Tracking and Risk Mitigation for Urban Autonomous DrivingCode1
Fourier Prompt Tuning for Modality-Incomplete Scene SegmentationCode1
Ford Multi-AV Seasonal DatasetCode1
Bootstrapping Autonomous Driving Radars with Self-Supervised LearningCode1
Robust super-resolution depth imaging via a multi-feature fusion deep networkCode1
CausalAgents: A Robustness Benchmark for Motion Forecasting using Causal RelationshipsCode1
GPT-4 Enhanced Multimodal Grounding for Autonomous Driving: Leveraging Cross-Modal Attention with Large Language ModelsCode1
Meta-RangeSeg: LiDAR Sequence Semantic Segmentation Using Multiple Feature AggregationCode1
BAAM: Monocular 3D Pose and Shape Reconstruction With Bi-Contextual Attention Module and Attention-Guided ModelingCode1
MonoProb: Self-Supervised Monocular Depth Estimation with Interpretable UncertaintyCode1
Multimodal Detection of Unknown Objects on Roads for Autonomous DrivingCode1
GndNet: Fast Ground Plane Estimation and Point Cloud Segmentation for Autonomous VehiclesCode1
S-AT GCN: Spatial-Attention Graph Convolution Network based Feature Enhancement for 3D Object DetectionCode1
Object Tracking by Detection with Visual and Motion CuesCode1
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Benchmark Results

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