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 2051–2100 of 6092 papers

TitleStatusHype
Visual Foundation Models Boost Cross-Modal Unsupervised Domain Adaptation for 3D Semantic SegmentationCode1
Real-Time Image Segmentation via Hybrid Convolutional-Transformer Architecture SearchCode1
Gradient based Feature Attribution in Explainable AI: A Technical Review—0
RCooper: A Real-world Large-scale Dataset for Roadside Cooperative PerceptionCode2
Enhancing Human-Centered Dynamic Scene Understanding via Multiple LLMs Collaborated Reasoning—0
On STPA for Distributed Development of Safe Autonomous Driving: An Interview Study—0
E2E-MFD: Towards End-to-End Synchronous Multimodal Fusion DetectionCode2
PreSight: Enhancing Autonomous Vehicle Perception with City-Scale NeRF PriorsCode1
GenAD: Generalized Predictive Model for Autonomous DrivingCode7
Intention-aware Denoising Diffusion Model for Trajectory Prediction—0
Are you a robot? Detecting Autonomous Vehicles from Behavior Analysis—0
Metasurface-Enabled Multifunctional Single-Frequency Sensors without External Power—0
FogGuard: guarding YOLO against fog using perceptual lossCode0
CLIP-BEVFormer: Enhancing Multi-View Image-Based BEV Detector with Ground Truth Flow—0
Optimized Detection and Classification on GTRSB: Advancing Traffic Sign Recognition with Convolutional Neural Networks—0
Offboard Occupancy Refinement with Hybrid Propagation for Autonomous DrivingCode1
MIM4D: Masked Modeling with Multi-View Video for Autonomous Driving Representation LearningCode2
Real-time 3D semantic occupancy prediction for autonomous vehicles using memory-efficient sparse convolution—0
LIX: Implicitly Infusing Spatial Geometric Prior Knowledge into Visual Semantic Segmentation for Autonomous Driving—0
DeepCSHAP: Utilizing Shapley Values to Explain Deep Complex-Valued Neural Networks—0
Adaptive Fusion of Single-View and Multi-View Depth for Autonomous DrivingCode2
Adaptive Bounding Box Uncertainties via Two-Step Conformal PredictionCode1
A Survey of Vision Transformers in Autonomous Driving: Current Trends and Future Directions—0
Unleashing HyDRa: Hybrid Fusion, Depth Consistency and Radar for Unified 3D PerceptionCode1
Tractable Joint Prediction and Planning over Discrete Behavior Modes for Urban Driving—0
People Attribute Purpose to Autonomous Vehicles When Explaining Their Behavior: Insights from Cognitive Science for Explainable AICode0
PCLD: Point Cloud Layerwise Diffusion for Adversarial PurificationCode0
DriveDreamer-2: LLM-Enhanced World Models for Diverse Driving Video GenerationCode3
SeSame: Simple, Easy 3D Object Detection with Point-Wise SemanticsCode1
On depth prediction for autonomous driving using self-supervised learning—0
Cross-Cluster Shifting for Efficient and Effective 3D Object Detection in Autonomous Driving—0
SAFDNet: A Simple and Effective Network for Fully Sparse 3D Object DetectionCode2
Fast Kernel Scene FlowCode1
Lightning NeRF: Efficient Hybrid Scene Representation for Autonomous DrivingCode2
JointMotion: Joint Self-Supervision for Joint Motion Prediction—0
LanePtrNet: Revisiting Lane Detection as Point Voting and Grouping on Curves—0
LVIC: Multi-modality segmentation by Lifting Visual Info as Cue—0
OccFusion: Depth Estimation Free Multi-sensor Fusion for 3D Occupancy Prediction—0
DyRoNet: Dynamic Routing and Low-Rank Adapters for Autonomous Driving Streaming Perception—0
FriendNet: Detection-Friendly Dehazing NetworkCode1
Embodied Understanding of Driving ScenariosCode3
LitSim: A Conflict-aware Policy for Long-term Interactive Traffic Simulation—0
Towards learning-based planning:The nuPlan benchmark for real-world autonomous driving—0
Generalizing Cooperative Eco-driving via Multi-residual Task Learning—0
Fooling Neural Networks for Motion Forecasting via Adversarial Attacks—0
Levels of AI Agents: from Rules to Large Language Models—0
Multi-Object Tracking with Camera-LiDAR Fusion for Autonomous Driving—0
Learning Adversarial MDPs with Stochastic Hard Constraints—0
3D Object Visibility Prediction in Autonomous Driving—0
Multi-task Learning for Real-time Autonomous Driving Leveraging Task-adaptive Attention Generator—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