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 2461–2470 of 2605 papers

TitleStatusHype
Building Prior Knowledge: A Markov Based Pedestrian Prediction Model Using Urban Environmental Data—0
Focal Loss in 3D Object DetectionCode0
A New Multi-vehicle Trajectory Generator to Simulate Vehicle-to-Vehicle Encounters—0
DLO: Direct LiDAR Odometry for 2.5D Outdoor Environment—0
Socially Aware Kalman Neural Networks for Trajectory Prediction—0
Adversarial Examples: Opportunities and Challenges—0
Adapting Semantic Segmentation Models for Changes in Illumination and Camera Perspective—0
CM3: Cooperative Multi-goal Multi-stage Multi-agent Reinforcement LearningCode0
Humans can decipher adversarial images—0
URBAN-i: From urban scenes to mapping slums, transport modes, and pedestrians in cities using deep learning and computer vision—0
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Benchmark Results

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