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 51–60 of 2605 papers

TitleStatusHype
Distilling Diffusion Models to Efficient 3D LiDAR Scene CompletionCode2
CC-3DT: Panoramic 3D Object Tracking via Cross-Camera FusionCode2
Certified Human Trajectory PredictionCode2
DiLu: A Knowledge-Driven Approach to Autonomous Driving with Large Language ModelsCode2
DPFT: Dual Perspective Fusion Transformer for Camera-Radar-based Object DetectionCode2
CMX: Cross-Modal Fusion for RGB-X Semantic Segmentation with TransformersCode2
DC-Gaussian: Improving 3D Gaussian Splatting for Reflective Dash Cam VideosCode2
A Transfer Learning and Optimized CNN Based Intrusion Detection System for Internet of VehiclesCode2
Driving into the Future: Multiview Visual Forecasting and Planning with World Model for Autonomous DrivingCode2
Open-World Semantic Segmentation Including Class SimilarityCode2
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Benchmark Results

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