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 761–770 of 2605 papers

TitleStatusHype
Mitigating Covariate Shift in Imitation Learning for Autonomous Vehicles Using Latent Space Generative World Models—0
A Computer Vision Approach for Autonomous Cars to Drive Safe at Construction Zone—0
System-Level Performance Metrics Sensitivity of an Electrified Heavy-Duty Mobile Manipulator—0
Few-Shot Testing of Autonomous Vehicles with Scenario Similarity Learning—0
DAP-LED: Learning Degradation-Aware Priors with CLIP for Joint Low-light Enhancement and Deblurring—0
SSE: Multimodal Semantic Data Selection and Enrichment for Industrial-scale Data Assimilation—0
VCAT: Vulnerability-aware and Curiosity-driven Adversarial Training for Enhancing Autonomous Vehicle RobustnessCode0
Hypergraph-based Motion Generation with Multi-modal Interaction Relational Reasoning—0
Optical Flow Matters: an Empirical Comparative Study on Fusing Monocular Extracted Modalities for Better Steering—0
Safety Verification and Navigation for Autonomous Vehicles based on Signal Temporal Logic Constraints—0
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Benchmark Results

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