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 5026–5050 of 6092 papers

TitleStatusHype
DiffLO: Semantic-Aware LiDAR Odometry with Diffusion-Based Refinement—0
DiffMap: Enhancing Map Segmentation with Map Prior Using Diffusion Model—0
Diff-Net: Image Feature Difference based High-Definition Map Change Detection for Autonomous Driving—0
DiffPrompter: Differentiable Implicit Visual Prompts for Semantic-Segmentation in Adverse Conditions—0
DiffSSC: Semantic LiDAR Scan Completion using Denoising Diffusion Probabilistic Models—0
Diffusion-Augmented Depth Prediction with Sparse Annotations—0
Diffusion-based 3D Object Detection with Random Boxes—0
Diffusion-Based Generative Models for 3D Occupancy Prediction in Autonomous Driving—0
Diffusion-ES: Gradient-free Planning with Diffusion for Autonomous and Instruction-guided Driving—0
Diffusion Model for Planning: A Systematic Literature Review—0
Diffusion Models for Intelligent Transportation Systems: A Survey—0
Diffusion Models in 3D Vision: A Survey—0
DiffVLA: Vision-Language Guided Diffusion Planning for Autonomous Driving—0
Dilemma of the Artificial Intelligence Regulatory Landscape—0
LidaRF: Delving into Lidar for Neural Radiance Field on Street Scenes—0
DINO Pre-training for Vision-based End-to-end Autonomous Driving—0
DINO-SD: Champion Solution for ICRA 2024 RoboDepth Challenge—0
Dionysus: Recovering Scene Structures by Dividing Into Semantic Pieces—0
Direct Depth Learning Network for Stereo Matching—0
DirectShape: Direct Photometric Alignment of Shape Priors for Visual Vehicle Pose and Shape Estimation—0
Discover, Hallucinate, and Adapt: Open Compound Domain Adaptation for Semantic Segmentation—0
Discrete Contrastive Learning for Diffusion Policies in Autonomous Driving—0
Discrete-Event Controller Synthesis for Autonomous Systems with Deep-Learning Perception Components—0
Disengagement Cause-and-Effect Relationships Extraction Using an NLP Pipeline—0
Disentangling and Vectorization: A 3D Visual Perception Approach for Autonomous Driving Based on Surround-View Fisheye Cameras—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