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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 31–40 of 2605 papers

TitleStatusHype
Certified Human Trajectory PredictionCode2
SmartRefine: A Scenario-Adaptive Refinement Framework for Efficient Motion PredictionCode2
MonoOcc: Digging into Monocular Semantic Occupancy PredictionCode2
Open-World Semantic Segmentation Including Class SimilarityCode2
OccFusion: Multi-Sensor Fusion Framework for 3D Semantic Occupancy PredictionCode2
PC-NeRF: Parent-Child Neural Radiance Fields Using Sparse LiDAR Frames in Autonomous Driving EnvironmentsCode2
LiDAR-PTQ: Post-Training Quantization for Point Cloud 3D Object DetectionCode2
Driving into the Future: Multiview Visual Forecasting and Planning with World Model for Autonomous DrivingCode2
GPT-Driver: Learning to Drive with GPTCode2
DiLu: A Knowledge-Driven Approach to Autonomous Driving with Large Language ModelsCode2
Show:102550
← PrevPage 4 of 261Next →

Benchmark Results

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