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 5601–5650 of 6092 papers

TitleStatusHype
Bin-wise Temperature Scaling (BTS): Improvement in Confidence Calibration Performance through Simple Scaling Techniques—0
DeepBbox: Accelerating Precise Ground Truth Generation for Autonomous Driving Datasets—0
Texture Underfitting for Domain Adaptation—0
Class-balanced Grouping and Sampling for Point Cloud 3D Object DetectionCode0
Generic Tracking and Probabilistic Prediction Framework and Its Application in Autonomous Driving—0
Design Space of Behaviour Planning for Autonomous Driving—0
Efficient Deep Neural Networks—0
Cross-Enhancement Transform Two-Stream 3D ConvNets for Action Recognition—0
How far should self-driving cars see? Effect of observation range on vehicle self-localization—0
Fine-Grained Segmentation Networks: Self-Supervised Segmentation for Improved Long-Term Visual LocalizationCode0
Mono-SF: Multi-View Geometry Meets Single-View Depth for Monocular Scene Flow Estimation of Dynamic Traffic Scenes—0
Adversarial shape perturbations on 3D point cloudsCode0
To complete or to estimate, that is the question: A Multi-Task Approach to Depth Completion and Monocular Depth Estimation—0
Bypass Enhancement RGB Stream Model for Pedestrian Action Recognition of Autonomous Vehicles—0
A Multimodal Vision Sensor for Autonomous Driving—0
Benchmarking the Robustness of Semantic Segmentation Models—0
Decision making in dynamic and interactive environments based on cognitive hierarchy theory, Bayesian inference, and predictive control—0
Incremental Reinforcement Learning --- a New Continuous Reinforcement Learning Frame Based on Stochastic Differential Equation methods—0
Learning Guided Convolutional Network for Depth CompletionCode0
Scalable Place Recognition Under Appearance Change for Autonomous Driving—0
Video Stitching for Linear Camera Arrays—0
Orientation-aware Semantic Segmentation on Icosahedron SpheresCode0
Single Level Feature-to-Feature Forecasting with Deformable Convolutions—0
Dynamic Input for Deep Reinforcement Learning in Autonomous Driving—0
Object as Distribution—0
Effortless Deep Training for Traffic Sign Detection Using Templates and Arbitrary Natural ImagesCode0
Analyzing the Variety Loss in the Context of Probabilistic Trajectory Prediction—0
Conf-Net: Toward High-Confidence Dense 3D Point-Cloud with Error-Map PredictionCode0
Class-specific Anchoring Proposal for 3D Object Recognition in LIDAR and RGB Images—0
Speeding Up Iterative Closest Point Using Stochastic Gradient DescentCode0
Characterizing Attacks on Deep Reinforcement LearningCode0
Data augmentation with Symbolic-to-Real Image Translation GANs for Traffic Sign Recognition—0
Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is ComingCode0
Improved Reinforcement Learning through Imitation Learning Pretraining Towards Image-based Autonomous Driving—0
Autonomous Driving in the Lung using Deep Learning for Localization—0
Adversarial Sensor Attack on LiDAR-based Perception in Autonomous Driving—0
A General Framework for Uncertainty Estimation in Deep LearningCode0
Improving 3D Object Detection for Pedestrians with Virtual Multi-View Synthesis Orientation Estimation—0
S&CNet: Monocular Depth Completion for Autonomous Systems and 3D Reconstruction—0
A Survey of Deep Learning-based Object Detection—0
Adversarial Objects Against LiDAR-Based Autonomous Driving Systems—0
Utilizing Eye Gaze to Enhance the Generalization of Imitation Networks to Unseen Environments—0
3D Multi-Object Tracking: A Baseline and New Evaluation MetricsCode0
PhysGAN: Generating Physical-World-Resilient Adversarial Examples for Autonomous Driving—0
A Multi-Stage Clustering Framework for Automotive Radar Data—0
Large-scale, real-time visual-inertial localization revisited—0
Voxel-FPN: multi-scale voxel feature aggregation in 3D object detection from point clouds—0
End-to-End 3D-PointCloud Semantic Segmentation for Autonomous Driving—0
Large-scale 3D point cloud representations via graph inception networks with applications to autonomous driving—0
Probabilistic model predictive safety certification for learning-based control—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