SOTAVerified

Autonomous Driving

Autonomous driving is the task of driving a vehicle 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: Exploring the Limitations of Behavior Cloning for Autonomous Driving)

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 5326–5350 of 6092 papers

TitleStatusHype
High precision indoor positioning by means of LiDAR—0
High Precision Indoor Navigation for Autonomous Vehicles—0
3D Scene Geometry-Aware Constraint for Camera Localization with Deep Learning—0
From Simulation to Real World Maneuver Execution using Deep Reinforcement Learning—0
STINet: Spatio-Temporal-Interactive Network for Pedestrian Detection and Trajectory Prediction—0
View Invariant Human Body Detection and Pose Estimation from Multiple Depth Sensors—0
SurfelGAN: Synthesizing Realistic Sensor Data for Autonomous Driving—0
Trajectory Prediction for Autonomous Driving based on Multi-Head Attention with Joint Agent-Map Representation—0
UST: Unifying Spatio-Temporal Context for Trajectory Prediction in Autonomous Driving—0
Probabilistic End-to-End Vehicle Navigation in Complex Dynamic Environments with Multimodal Sensor Fusion—0
CoMoGCN: Coherent Motion Aware Trajectory Prediction with Graph Representation—0
Deep Reinforcement Learning for Intelligent Transportation Systems: A Survey—0
TS-MPC for Autonomous Vehicle using a Learning Approach—0
Psychophysical Evaluation of Deep Re-Identification Models—0
TPNet: Trajectory Proposal Network for Motion Prediction—0
ML-driven Malware that Targets AV Safety—0
Explicit Domain Adaptation with Loosely Coupled Samples—0
Cooperative Perception with Deep Reinforcement Learning for Connected Vehicles—0
CodNN -- Robust Neural Networks From Coded Classification—0
Distributed Learning and Inference with Compressed Images—0
3D Object Detection Method Based on YOLO and K-Means for Image and Point Clouds—0
Single-step Adversarial training with Dropout Scheduling—0
Realistic Large-Scale Fine-Depth Dehazing Dataset from 3D Videos—0
Efficient Synthesis of Compact Deep Neural Networks—0
Approximate Inverse Reinforcement Learning from Vision-based Imitation Learning—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ReasonNetDriving Score79.95—Unverified
2InterFuserDriving Score76.18—Unverified
3TCPDriving Score75.14—Unverified
4TF++ WPDriving Score66.32—Unverified
5Learning From All Vehicles (LAV)Driving Score61.85—Unverified
6TransFuserDriving Score61.18—Unverified
7TransFuser (Reproduced)Driving Score55.04—Unverified
8TCP (Reproduced)Driving Score47.91—Unverified
9Latent TransFuserDriving Score45.2—Unverified
10GRIADDriving Score36.79—Unverified
#ModelMetricClaimedVerifiedStatus
1Geometric FusionRC69.17—Unverified
2TransFuserRC56.36—Unverified
#ModelMetricClaimedVerifiedStatus
1Geometric FusionRC86.91—Unverified
2TransFuserRC78.41—Unverified