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 3351–3400 of 6092 papers

TitleStatusHype
Boosting Online 3D Multi-Object Tracking through Camera-Radar Cross Check—0
Boosting the Transferability of Adversarial Samples via Attention—0
BoostRad: Enhancing Object Detection by Boosting Radar Reflections—0
Bosch Deep Learning Hardware Benchmark—0
BoT-Drive: Hierarchical Behavior and Trajectory Planning for Autonomous Driving using POMDPs—0
BOTT: Box Only Transformer Tracker for 3D Object Tracking—0
Boundary-Guided Trajectory Prediction for Road Aware and Physically Feasible Autonomous Driving—0
BoundED: Neural Boundary and Edge Detection in 3D Point Clouds via Local Neighborhood Statistics—0
Bounding Boxes, Segmentations and Object Coordinates: How Important Is Recognition for 3D Scene Flow Estimation in Autonomous Driving Scenarios?—0
Box-level Segmentation Supervised Deep Neural Networks for Accurate and Real-time Multispectral Pedestrian Detection—0
Brain2Model Transfer: Training sensory and decision models with human neural activity as a teacher—0
Brain Inspired Cognitive Model with Attention for Self-Driving Cars—0
Bridging Data-Driven and Physics-Based Models: A Consensus Multi-Model Kalman Filter for Robust Vehicle State Estimation—0
Bridging the gap between Markowitz planning and deep reinforcement learning—0
Bridging the Gap Between Multi-Step and One-Shot Trajectory Prediction via Self-Supervision—0
Bridging the Gap between Real-world and Synthetic Images for Testing Autonomous Driving Systems—0
Bridging the Sim2Real gap with CARE: Supervised Detection Adaptation with Conditional Alignment and Reweighting—0
Bridging the View Disparity Between Radar and Camera Features for Multi-modal Fusion 3D Object Detection—0
Building Blocks for Robust and Effective Semi-Supervised Real-World Object Detection—0
Building Safer Autonomous Agents by Leveraging Risky Driving Behavior Knowledge—0
Burn-In Demonstrations for Multi-Modal Imitation Learning—0
Bypass Enhancement RGB Stream Model for Pedestrian Action Recognition of Autonomous Vehicles—0
C^2INet: Realizing Incremental Trajectory Prediction with Prior-Aware Continual Causal Intervention—0
CaDeT: a Causal Disentanglement Approach for Robust Trajectory Prediction in Autonomous Driving—0
CalibFormer: A Transformer-based Automatic LiDAR-Camera Calibration Network—0
Calibrated and Efficient Sampling-Free Confidence Estimation for LiDAR Scene Semantic Segmentation—0
Calibrating Uncertainties in Object Localization Task—0
Calibration Method of the Monocular Omnidirectional Stereo Camera—0
Calibration Regularized Training of Deep Neural Networks using Kernel Density Estimation—0
CalibRBEV: Multi-Camera Calibration via ReversedBird's-eye-view Representations for Autonomous Driving.—0
CALICO: Self-Supervised Camera-LiDAR Contrastive Pre-training for BEV Perception—0
Camera Agnostic Two-Head Network for Ego-Lane Inference—0
Camera-Based Localization and Enhanced Normalized Mutual Information—0
Camera-based vehicle velocity estimation from monocular video—0
Camera Calibration with Pose Guidance—0
CAML: Collaborative Auxiliary Modality Learning for Multi-Agent Systems—0
CamNet: Coarse-to-Fine Retrieval for Camera Re-Localization—0
CAMO-MOT: Combined Appearance-Motion Optimization for 3D Multi-Object Tracking with Camera-LiDAR Fusion—0
Can LLMs Understand Social Norms in Autonomous Driving Games?—0
Can LVLMs Obtain a Driver's License? A Benchmark Towards Reliable AGI for Autonomous Driving—0
Can Transformer Attention Spread Give Insights Into Uncertainty of Detected and Tracked Objects?—0
Can Vision-Language Models Understand and Interpret Dynamic Gestures from Pedestrians? Pilot Datasets and Exploration Towards Instructive Nonverbal Commands for Cooperative Autonomous Vehicles—0
Can We Trust You? On Calibration of a Probabilistic Object Detector for Autonomous Driving—0
Can we unify monocular detectors for autonomous driving by using the pixel-wise semantic segmentation of CNNs?—0
Can you text what is happening? Integrating pre-trained language encoders into trajectory prediction models for autonomous driving—0
CAPS: Context-Aware Priority Sampling for Enhanced Imitation Learning in Autonomous Driving—0
Capsule Neural Network based Height Classification using Low-Cost Automotive Ultrasonic Sensors—0
Capture Uncertainties in Deep Neural Networks for Safe Operation of Autonomous Driving Vehicles—0
CaRaFFusion: Improving 2D Semantic Segmentation with Camera-Radar Point Cloud Fusion and Zero-Shot Image Inpainting—0
CARFF: Conditional Auto-encoded Radiance Field for 3D Scene Forecasting—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