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 4126–4150 of 6092 papers

TitleStatusHype
Extending One-Stage Detection with Open-World Proposals—0
Extending Silicon Lifetime: A Review of Design Techniques for Reliable Integrated Circuits—0
Extraction and Assessment of Naturalistic Human Driving Trajectories from Infrastructure Camera and Radar Sensors—0
EyeDAS: Securing Perception of Autonomous Cars Against the Stereoblindness Syndrome—0
Factors of Influence for Transfer Learning across Diverse Appearance Domains and Task Types—0
Failure Detection for Motion Prediction of Autonomous Driving: An Uncertainty Perspective—0
Failure Prediction for Autonomous Driving—0
Failure-Scenario Maker for Rule-Based Agent using Multi-agent Adversarial Reinforcement Learning and its Application to Autonomous Driving—0
FALCON: Frequency Adjoint Link with CONtinuous Density Mask for Fast Single Image Dehazing—0
FASIONAD : FAst and Slow FusION Thinking Systems for Human-Like Autonomous Driving with Adaptive Feedback—0
FASIONAD++ : Integrating High-Level Instruction and Information Bottleneck in FAt-Slow fusION Systems for Enhanced Safety in Autonomous Driving with Adaptive Feedback—0
FAST3D: Flow-Aware Self-Training for 3D Object Detectors—0
Fast and Accurate Object Detection on Asymmetrical Receptive Field—0
Fast and Efficient Scene Categorization for Autonomous Driving using VAEs—0
Fast-Convergent and Communication-Alleviated Heterogeneous Hierarchical Federated Learning in Autonomous Driving—0
Fast-COS: A Fast One-Stage Object Detector Based on Reparameterized Attention Vision Transformer for Autonomous Driving—0
Faster and Smarter AutoAugment: Augmentation Policy Search Based on Dynamic Data-Clustering—0
FLIC: Fast Lidar Image Clustering—0
FastOcc: Accelerating 3D Occupancy Prediction by Fusing the 2D Bird's-Eye View and Perspective View—0
Fast Occupancy Network—0
Fast Quantum Convolutional Neural Networks for Low-Complexity Object Detection in Autonomous Driving Applications—0
Fast Recurrent Fully Convolutional Networks for Direct Perception in Autonomous Driving—0
Fast-Spherical-Projection-Based Point Cloud Clustering Algorithm—0
Fault-Aware Design and Training to Enhance DNNs Reliability with Zero-Overhead—0
SGD: Street View Synthesis with Gaussian Splatting and Diffusion Prior—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