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

Showing 381390 of 2605 papers

TitleStatusHype
An Efficient Approach to Generate Safe Drivable Space by LiDAR-Camera-HDmap FusionCode1
Persistent Map Saving for Visual Localization for Autonomous Vehicles: An ORB-SLAM ExtensionCode1
CRAT-Pred: Vehicle Trajectory Prediction with Crystal Graph Convolutional Neural Networks and Multi-Head Self-AttentionCode1
DSLR: Dynamic to Static LiDAR Scan Reconstruction Using Adversarially Trained AutoencoderCode1
HM-ViT: Hetero-modal Vehicle-to-Vehicle Cooperative perception with vision transformerCode1
Pylot: A Modular Platform for Exploring Latency-Accuracy Tradeoffs in Autonomous VehiclesCode1
Probabilistic 3D Multi-Object Cooperative Tracking for Autonomous Driving via Differentiable Multi-Sensor Kalman FilterCode1
Radar-STDA: A High-Performance Spatial-Temporal Denoising Autoencoder for Interference Mitigation of FMCW RadarsCode1
RangeNet++: Fast and Accurate LiDAR Semantic SegmentationCode1
VG-SSL: Benchmarking Self-supervised Representation Learning Approaches for Visual Geo-localizationCode1
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Benchmark Results

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