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 5160 of 2605 papers

TitleStatusHype
Driving into the Future: Multiview Visual Forecasting and Planning with World Model for Autonomous DrivingCode2
DC-Gaussian: Improving 3D Gaussian Splatting for Reflective Dash Cam VideosCode2
DiLu: A Knowledge-Driven Approach to Autonomous Driving with Large Language ModelsCode2
DriVLMe: Enhancing LLM-based Autonomous Driving Agents with Embodied and Social ExperiencesCode2
GSPR: Multimodal Place Recognition Using 3D Gaussian Splatting for Autonomous DrivingCode2
SegNet4D: Efficient Instance-Aware 4D Semantic Segmentation for LiDAR Point CloudCode2
CC-3DT: Panoramic 3D Object Tracking via Cross-Camera FusionCode2
Certified Human Trajectory PredictionCode2
ChatScene: Knowledge-Enabled Safety-Critical Scenario Generation for Autonomous VehiclesCode2
OpenLane-V2: A Topology Reasoning Benchmark for Unified 3D HD MappingCode2
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Benchmark Results

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