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 1401–1410 of 2605 papers

TitleStatusHype
S2TNet: Spatio-Temporal Transformer Networks for Trajectory Prediction in Autonomous DrivingCode1
CoCoPIE XGen: A Full-Stack AI-Oriented Optimizing Framework—0
Demystifying the Adversarial Robustness of Random Transformation DefensesCode0
Holistic Transformer: A Joint Neural Network for Trajectory Prediction and Decision-Making of Autonomous Vehicles—0
A Comprehensive Eco-Driving Strategy for Connected and Autonomous Vehicles (CAVs) with Microscopic Traffic Simulation Testing Evaluation—0
Online Segmentation of LiDAR Sequences: Dataset and AlgorithmCode1
Simple-BEV: What Really Matters for Multi-Sensor BEV Perception?—0
Waymo Open Dataset: Panoramic Video Panoptic Segmentation—0
Energy Consumption Analysis of pruned Semantic Segmentation Networks on an Embedded GPUCode0
Receding Moving Object Segmentation in 3D LiDAR Data Using Sparse 4D ConvolutionsCode2
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Benchmark Results

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