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 661–670 of 2605 papers

TitleStatusHype
Segment-Level Road Obstacle Detection Using Visual Foundation Model Priors and Likelihood Ratios—0
Text to Blind Motion—0
VTD: Visual and Tactile Database for Driver State and Behavior Perception—0
LaserGuider: A Laser Based Physical Backdoor Attack against Deep Neural Networks—0
UNCOVER: Unknown Class Object Detection for Autonomous Vehicles in Real-time—0
Reinforcement Learning for Freeway Lane-Change Regulation via Connected Vehicles—0
Generating Critical Scenarios for Testing Automated Driving Systems—0
FoveaSPAD: Exploiting Depth Priors for Adaptive and Efficient Single-Photon 3D Imaging—0
ILASH: A Predictive Neural Architecture Search Framework for Multi-Task Applications—0
On Privacy, Security, and Trustworthiness in Distributed Wireless Large AI Models (WLAM)—0
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Benchmark Results

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