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 3476–3500 of 6092 papers

TitleStatusHype
Combating Partial Perception Deficit in Autonomous Driving with Multimodal LLM Commonsense—0
Combining Belief Function Theory and Stochastic Model Predictive Control for Multi-Modal Uncertainty in Autonomous Driving—0
Combining Planning and Deep Reinforcement Learning in Tactical Decision Making for Autonomous Driving—0
Common Corruption Robustness of Point Cloud Detectors: Benchmark and Enhancement—0
Common Sense Is All You Need—0
Commonsense Visual Sensemaking for Autonomous Driving: On Generalised Neurosymbolic Online Abduction Integrating Vision and Semantics—0
Communication-Aware Consistent Edge Selection for Mobile Users and Autonomous Vehicles—0
Communication Efficient Cooperative Edge AI via Event-Triggered Computation Offloading—0
Communication-Efficient MARL for Platoon Stability and Energy-efficiency Co-optimization in Cooperative Adaptive Cruise Control of CAVs—0
CoMoGCN: Coherent Motion Aware Trajectory Prediction with Graph Representation—0
Comparative Study of Q-Learning and NeuroEvolution of Augmenting Topologies for Self Driving Agents—0
Comparison of Pedestrian Prediction Models from Trajectory and Appearance Data for Autonomous Driving—0
Comparison of Source Coding Techniques for the Vehicle to Vehicle Communication—0
Complete Solution for Vehicle Re-ID in Surround-view Camera System—0
Complexer-YOLO: Real-Time 3D Object Detection and Tracking on Semantic Point Clouds—0
Complex-valued Convolutional Neural Networks for Enhanced Radar Signal Denoising and Interference Mitigation—0
Composing Meta-Policies for Autonomous Driving Using Hierarchical Deep Reinforcement Learning—0
Comprehensive Overview of Reward Engineering and Shaping in Advancing Reinforcement Learning Applications—0
Compressing Deep Reinforcement Learning Networks with a Dynamic Structured Pruning Method for Autonomous Driving—0
Compressive Change Retrieval for Moving Object Detection—0
Computer Stereo Vision for Autonomous Driving—0
Computer Vision for Autonomous Vehicles: Problems, Datasets and State of the Art—0
Computer vision in automated parking systems: Design, implementation and challenges—0
Overview of Computer Vision Techniques in Robotized Wire Harness Assembly: Current State and Future Opportunities—0
Conditional Generative Adversarial Network for Structured Domain Adaptation—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