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
Socially Aware Kalman Neural Networks for Trajectory Prediction—0
Adversarial Examples: Opportunities and Challenges—0
CM3: Cooperative Multi-goal Multi-stage Multi-agent Reinforcement LearningCode0
Adapting Semantic Segmentation Models for Changes in Illumination and Camera Perspective—0
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
Towards a Fatality-Aware Benchmark of Probabilistic Reaction Prediction in Highly Interactive Driving Scenarios—0
Probabilistic Prediction of Interactive Driving Behavior via Hierarchical Inverse Reinforcement Learning—0
Eliminating the Blind Spot: Adapting 3D Object Detection and Monocular Depth Estimation to 360° Panoramic Imagery—0
JuncNet: A Deep Neural Network for Road Junction Disambiguation for Autonomous Vehicles—0
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Benchmark Results

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