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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 2551–2560 of 2605 papers

TitleStatusHype
End-to-End Deep Learning for Steering Autonomous Vehicles Considering Temporal Dependencies—0
Socially Compliant Navigation through Raw Depth Inputs with Generative Adversarial Imitation LearningCode0
Detecting Adversarial Attacks on Neural Network Policies with Visual ForesightCode0
Cooperative Automated Vehicles: a Review of Opportunities and Challenges in Socially Intelligent Vehicles Beyond Networking—0
Extracting Traffic Primitives Directly from Naturalistically Logged Data for Self-Driving Applications—0
Fully Convolutional Neural Networks for Dynamic Object Detection in Grid Maps (Masters Thesis)—0
Towards Proving the Adversarial Robustness of Deep Neural Networks—0
Proceedings First Workshop on Formal Verification of Autonomous Vehicles—0
DeepTest: Automated Testing of Deep-Neural-Network-driven Autonomous CarsCode0
Resilient Linear Classification: An Approach to Deal with Attacks on Training Data—0
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Benchmark Results

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