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 2521–2530 of 2605 papers

TitleStatusHype
On the Importance of Stereo for Accurate Depth Estimation: An Efficient Semi-Supervised Deep Neural Network ApproachCode0
HATS: Histograms of Averaged Time Surfaces for Robust Event-based Object ClassificationCode0
MIRIAM: A Multimodal Chat-Based Interface for Autonomous Systems—0
Localization under Topological Uncertainty for Lane Identification of Autonomous Vehicles—0
Multi-Agent Imitation Learning for Driving SimulationCode0
Mono-Camera 3D Multi-Object Tracking Using Deep Learning Detections and PMBM Filtering—0
Optimal Control of Autonomous Vehicles Approaching A Traffic Light—0
No Blind Spots: Full-Surround Multi-Object Tracking for Autonomous Vehicles using Cameras & LiDARsCode0
Tracking Noisy Targets: A Review of Recent Object Tracking Approaches—0
Driver Gaze Zone Estimation using Convolutional Neural Networks: A General Framework and Ablative Analysis—0
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Benchmark Results

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