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 126–150 of 2605 papers

TitleStatusHype
Parameterized Decision-making with Multi-modal Perception for Autonomous DrivingCode1
Personalized Autonomous Driving with Large Language Models: Field ExperimentsCode1
Reliability in Semantic Segmentation: Can We Use Synthetic Data?Code1
Efficient Object Detection in Autonomous Driving using Spiking Neural Networks: Performance, Energy Consumption Analysis, and Insights into Open-set Object DiscoveryCode1
TULIP: Transformer for Upsampling of LiDAR Point CloudsCode1
BAT: Behavior-Aware Human-Like Trajectory Prediction for Autonomous DrivingCode1
Bootstrapping Autonomous Driving Radars with Self-Supervised LearningCode1
GPT-4 Enhanced Multimodal Grounding for Autonomous Driving: Leveraging Cross-Modal Attention with Large Language ModelsCode1
Dolphins: Multimodal Language Model for DrivingCode1
MonoProb: Self-Supervised Monocular Depth Estimation with Interpretable UncertaintyCode1
Automated Lane Change via Adaptive Interactive MPC: Human-in-the-Loop ExperimentsCode1
LCPR: A Multi-Scale Attention-Based LiDAR-Camera Fusion Network for Place RecognitionCode1
JRDB-Traj: A Dataset and Benchmark for Trajectory Forecasting in CrowdsCode1
Learning Cooperative Trajectory Representations for Motion ForecastingCode1
RGB-X Object Detection via Scene-Specific Fusion ModulesCode1
Reward Finetuning for Faster and More Accurate Unsupervised Object DiscoveryCode1
CityRefer: Geography-aware 3D Visual Grounding Dataset on City-scale Point Cloud DataCode1
Safe Navigation: Training Autonomous Vehicles using Deep Reinforcement Learning in CARLACode1
LiDAR-based 4D Occupancy Completion and ForecastingCode1
DUSA: Decoupled Unsupervised Sim2Real Adaptation for Vehicle-to-Everything Collaborative PerceptionCode1
PC-NeRF: Parent-Child Neural Radiance Fields under Partial Sensor Data Loss in Autonomous Driving EnvironmentsCode1
MotionLM: Multi-Agent Motion Forecasting as Language ModelingCode1
Semantic Map Learning of Traffic Light to Lane Assignment based on Motion DataCode1
Probabilistic 3D Multi-Object Cooperative Tracking for Autonomous Driving via Differentiable Multi-Sensor Kalman FilterCode1
Scene Informer: Anchor-based Occlusion Inference and Trajectory Prediction in Partially Observable EnvironmentsCode1
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Benchmark Results

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