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 2130 of 2605 papers

TitleStatusHype
SeFlow: A Self-Supervised Scene Flow Method in Autonomous DrivingCode2
SegNet4D: Efficient Instance-Aware 4D Semantic Segmentation for LiDAR Point CloudCode2
DriVLMe: Enhancing LLM-based Autonomous Driving Agents with Embodied and Social ExperiencesCode2
FedPylot: Navigating Federated Learning for Real-Time Object Detection in Internet of VehiclesCode2
DC-Gaussian: Improving 3D Gaussian Splatting for Reflective Dash Cam VideosCode2
ChatScene: Knowledge-Enabled Safety-Critical Scenario Generation for Autonomous VehiclesCode2
3D LiDAR Mapping in Dynamic Environments Using a 4D Implicit Neural RepresentationCode2
Toward Unified Practices in Trajectory Prediction Research on Bird's-Eye-View DatasetsCode2
VBR: A Vision Benchmark in RomeCode2
DPFT: Dual Perspective Fusion Transformer for Camera-Radar-based Object DetectionCode2
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Benchmark Results

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