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 641–650 of 2605 papers

TitleStatusHype
EP-Diffuser: An Efficient Diffusion Model for Traffic Scene Generation and Prediction via Polynomial RepresentationsCode0
Enhanced free space detection in multiple lanes based on single CNN with scene identificationCode0
Enhancing Object Detection for Autonomous Driving by Optimizing Anchor Generation and Addressing Class ImbalanceCode0
EpiTESTER: Testing Autonomous Vehicles with Epigenetic Algorithm and Attention MechanismCode0
End-to-end Learning of Image based Lane-Change DecisionCode0
Embedded real-time stereo estimation via Semi-Global Matching on the GPUCode0
Eliminating the Blind Spot: Adapting 3D Object Detection and Monocular Depth Estimation to 360° Panoramic ImageryCode0
Energy Consumption Analysis of pruned Semantic Segmentation Networks on an Embedded GPUCode0
A Lightweight Modular Framework for Low-Cost Open-Vocabulary Object Detection TrainingCode0
Failing to Learn: Autonomously Identifying Perception Failures for Self-driving CarsCode0
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Benchmark Results

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