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 681–690 of 2605 papers

TitleStatusHype
Detecting Out-of-distribution Objects Using Neuron Activation PatternsCode0
Depth- and Semantics-aware Multi-modal Domain Translation: Generating 3D Panoramic Color Images from LiDAR Point CloudsCode0
DepthNet: Real-Time LiDAR Point Cloud Depth Completion for Autonomous VehiclesCode0
Demystifying the Adversarial Robustness of Random Transformation DefensesCode0
A Robust Road Vanishing Point Detection Adapted to the Real-World Driving ScenesCode0
DeepTest: Automated Testing of Deep-Neural-Network-driven Autonomous CarsCode0
Driver Identification Based on Vehicle Telematics Data using LSTM-Recurrent Neural NetworkCode0
Enhanced free space detection in multiple lanes based on single CNN with scene identificationCode0
Game-theoretic Objective Space PlanningCode0
Real-time 3D Traffic Cone Detection for Autonomous DrivingCode0
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Benchmark Results

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