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 871–880 of 2605 papers

TitleStatusHype
LCPR: A Multi-Scale Attention-Based LiDAR-Camera Fusion Network for Place RecognitionCode1
Scenario Diffusion: Controllable Driving Scenario Generation With Diffusion—0
JRDB-Traj: A Dataset and Benchmark for Trajectory Forecasting in CrowdsCode1
From Chaos to Calibration: A Geometric Mutual Information Approach to Target-Free Camera LiDAR Extrinsic Calibration—0
Multi-LiDAR Localization and Mapping Pipeline for Urban Autonomous Driving—0
Adversary ML Resilience in Autonomous Driving Through Human Centered Perception Mechanisms—0
DRNet: A Decision-Making Method for Autonomous Lane Changingwith Deep Reinforcement Learning—0
Learning Cooperative Trajectory Representations for Motion ForecastingCode1
Safety-aware Causal Representation for Trustworthy Offline Reinforcement Learning in Autonomous Driving—0
Decision-Making for Autonomous Vehicles with Interaction-Aware Behavioral Prediction and Social-Attention Neural Network—0
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Benchmark Results

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