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

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Showing 6001–6050 of 6092 papers

TitleStatusHype
Learning Ordinality in Semantic Segmentation—0
Learning Pedestrian Actions to Ensure Safe Autonomous Driving—0
Learning Personalized Discretionary Lane-Change Initiation for Fully Autonomous Driving Based on Reinforcement Learning—0
Learning predictive representations in autonomous driving to improve deep reinforcement learning—0
Learning Progressive Point Embeddings for 3D Point Cloud Generation—0
Effects of Multimodal Explanations for Autonomous Driving on Driving Performance, Cognitive Load, Expertise, Confidence, and Trust—0
Learning Rank-1 Diffractive Optics for Single-Shot High Dynamic Range Imaging—0
Learning Representation for Anomaly Detection of Vehicle Trajectories—0
Learning Residual Model of Model Predictive Control via Random Forests for Autonomous Driving—0
Learning Resilient Behaviors for Navigation Under Uncertainty—0
Learning responsibility allocations for multi-agent interactions: A differentiable optimization approach with control barrier functions—0
Learning Rewards to Optimize Global Performance Metrics in Deep Reinforcement Learning—0
A Game-Theoretic Framework for Managing Risk in Multi-Agent Systems—0
Learning Sampling Dictionaries for Efficient and Generalizable Robot Motion Planning with Transformers—0
Learning Spatial and Temporal Variations for 4D Point Cloud Segmentation—0
Learning Stability Attention in Vision-based End-to-end Driving Policies—0
Learning Stixel-based Instance Segmentation—0
Learning Super-resolved Depth from Active Gated Imaging—0
Learning Temporal 3D Semantic Scene Completion via Optical Flow Guidance—0
Learning Temporal Cues by Predicting Objects Move for Multi-camera 3D Object Detection—0
Learning Terrain-Aware Kinodynamic Model for Autonomous Off-Road Rally Driving With Model Predictive Path Integral Control—0
Learning to Anticipate Egocentric Actions by Imagination—0
Learning to Collide: An Adaptive Safety-Critical Scenarios Generating Method—0
Realistic Large-Scale Fine-Depth Dehazing Dataset from 3D Videos—0
Learning to Drive Anywhere—0
Learning to Drive by Imitating Surrounding Vehicles—0
Learning to Drive by Observing the Best and Synthesizing the Worst—0
Learning to Drive using Inverse Reinforcement Learning and Deep Q-Networks—0
Learning to Drive Using Sparse Imitation Reinforcement Learning—0
Learning to falsify automated driving vehicles with prior knowledge—0
Learning to Influence Human Behavior with Offline Reinforcement Learning—0
Learning to Model Diverse Driving Behaviors in Highly Interactive Autonomous Driving Scenarios with Multi-Agent Reinforcement Learning—0
Learning to Optimize Autonomy in Competence-Aware Systems—0
Learning to Predict Vehicle Trajectories with Model-based Planning—0
Learning to Rank for Active Learning: A Listwise Approach—0
Learning to Robustly Negotiate Bi-Directional Lane Usage in High-Conflict Driving Scenarios—0
Learning to Switch Among Agents in a Team via 2-Layer Markov Decision Processes—0
Learning to Track: Online Multi-Object Tracking by Decision Making—0
Energy-Based Continuous Inverse Optimal Control—0
Learning Uncertainty For Safety-Oriented Semantic Segmentation In Autonomous Driving—0
Copilot4D: Learning Unsupervised World Models for Autonomous Driving via Discrete Diffusion—0
Learning with Chemical versus Electrical Synapses -- Does it Make a Difference?—0
Learning without Knowing: Unobserved Context in Continuous Transfer Reinforcement Learning—0
Learning with Style: Continual Semantic Segmentation Across Tasks and Domains—0
Learn-to-Race Challenge 2022: Benchmarking Safe Learning and Cross-domain Generalisation in Autonomous Racing—0
LEGO-Motion: Learning-Enhanced Grids with Occupancy Instance Modeling for Class-Agnostic Motion Prediction—0
LENVIZ: A High-Resolution Low-Exposure Night Vision Benchmark Dataset—0
Training Data Subset Search with Ensemble Active Learning—0
Less is More: A Stealthy and Efficient Adversarial Attack Method for DRL-based Autonomous Driving Policies—0
Less is More: Efficient Brain-Inspired Learning for Autonomous Driving Trajectory Prediction—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