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 126150 of 2605 papers

TitleStatusHype
Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road ScenesCode1
CausalAgents: A Robustness Benchmark for Motion Forecasting using Causal RelationshipsCode1
Evaluating Adversarial Attacks on Driving Safety in Vision-Based Autonomous VehiclesCode1
Explaining Autonomous Driving Actions with Visual Question AnsweringCode1
Energy-based Detection of Adverse Weather Effects in LiDAR DataCode1
Bootstrapping Autonomous Driving Radars with Self-Supervised LearningCode1
3D-MiniNet: Learning a 2D Representation from Point Clouds for Fast and Efficient 3D LIDAR Semantic SegmentationCode1
Monitoring and Adapting the Physical State of a Camera for Autonomous VehiclesCode1
Enhanced Laser-Scan Matching with Online Error Estimation for Highway and Tunnel DrivingCode1
Towards Motion Forecasting with Real-World Perception Inputs: Are End-to-End Approaches Competitive?Code1
BirdNet+: End-to-End 3D Object Detection in LiDAR Bird's Eye ViewCode1
Emergent Road Rules In Multi-Agent Driving EnvironmentsCode1
BirdNet: a 3D Object Detection Framework from LiDAR informationCode1
End-to-end Lane Shape Prediction with TransformersCode1
Enhancing Safety in Mixed Traffic: Learning-Based Modeling and Efficient Control of Autonomous and Human-Driven VehiclesCode1
Adaptive-Mask Fusion Network for Segmentation of Drivable Road and Negative Obstacle With Untrustworthy FeaturesCode1
Dynamic 3D Scene Analysis by Point Cloud AccumulationCode1
Efficient and Effective Generation of Test Cases for Pedestrian Detection -- Search-based Software Testing of Baidu Apollo in SVLCode1
BAT: Behavior-Aware Human-Like Trajectory Prediction for Autonomous DrivingCode1
DSLR: Dynamic to Static LiDAR Scan Reconstruction Using Adversarially Trained AutoencoderCode1
DUSA: Decoupled Unsupervised Sim2Real Adaptation for Vehicle-to-Everything Collaborative PerceptionCode1
Efficient Motion Prediction: A Lightweight & Accurate Trajectory Prediction Model With Fast Training and Inference SpeedCode1
AVP-SLAM: Semantic Visual Mapping and Localization for Autonomous Vehicles in the Parking LotCode1
BAAM: Monocular 3D Pose and Shape Reconstruction With Bi-Contextual Attention Module and Attention-Guided ModelingCode1
Autonomous Racing using a Hybrid Imitation-Reinforcement Learning ArchitectureCode1
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Benchmark Results

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