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 591–600 of 2605 papers

TitleStatusHype
FedRSU: Federated Learning for Scene Flow Estimation on Roadside UnitsCode0
Generative AI-empowered Simulation for Autonomous Driving in Vehicular Mixed Reality MetaversesCode0
FIR-based Future Trajectory Prediction in Nighttime Autonomous DrivingCode0
GCP: Guarded Collaborative Perception with Spatial-Temporal Aware Malicious Agent DetectionCode0
Harnessing Multi-resolution and Multi-scale Attention for Underwater Image RestorationCode0
Cooperation-Aware Reinforcement Learning for Merging in Dense TrafficCode0
Fast Deep Stereo with 2D Convolutional Processing of Cost SignaturesCode0
Convolutional Neural Network-based Intrusion Detection System for AVTP Streams in Automotive Ethernet-based NetworksCode0
MEDIRL: Predicting the Visual Attention of Drivers via Maximum Entropy Deep Inverse Reinforcement LearningCode0
Extending Structural Causal Models for Autonomous Vehicles to Simplify Temporal System Construction & Enable Dynamic Interactions Between AgentsCode0
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Benchmark Results

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