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 5551–5575 of 6092 papers

TitleStatusHype
LiDAR-EDIT: LiDAR Data Generation by Editing the Object Layouts in Real-World Scenes—0
Generative Model-Based Fusion for Improved Few-Shot Semantic Segmentation of Infrared Images—0
Generative One-Shot Learning (GOL): A Semi-Parametric Approach to One-Shot Learning in Autonomous Vision—0
Generic Probabilistic Interactive Situation Recognition and Prediction: From Virtual to Real—0
Generic Tracking and Probabilistic Prediction Framework and Its Application in Autonomous Driving—0
Generic Vehicle Tracking Framework Capable of Handling Occlusions Based on Modified Mixture Particle Filter—0
GENESIS-RL: GEnerating Natural Edge-cases with Systematic Integration of Safety considerations and Reinforcement Learning—0
GenFollower: Enhancing Car-Following Prediction with Large Language Models—0
GenMM: Geometrically and Temporally Consistent Multimodal Data Generation for Video and LiDAR—0
GEOcc: Geometrically Enhanced 3D Occupancy Network with Implicit-Explicit Depth Fusion and Contextual Self-Supervision—0
Geo-Context Aware Study of Vision-Based Autonomous Driving Models and Spatial Video Data—0
Geo-locating Road Objects using Inverse Haversine Formula with NVIDIA Driveworks—0
Exploring Geometric Consistency for Monocular 3D Object Detection—0
Geometry-Aware Video Object Detection for Static Cameras—0
Geometry-Based Next Frame Prediction from Monocular Video—0
Geometry-based Occlusion-Aware Unsupervised Stereo Matching for Autonomous Driving—0
Geometry-Constrained Monocular Scale Estimation Using Semantic Segmentation for Dynamic Scenes—0
GeomGS: LiDAR-Guided Geometry-Aware Gaussian Splatting for Robot Localization—0
Get a Model! Model Hijacking Attack Against Machine Learning Models—0
GFD-SSD: Gated Fusion Double SSD for Multispectral Pedestrian Detection—0
GGS: Generalizable Gaussian Splatting for Lane Switching in Autonomous Driving—0
GIDP: Learning a Good Initialization and Inducing Descriptor Post-enhancing for Large-scale Place Recognition—0
GINA-3D: Learning to Generate Implicit Neural Assets in the Wild—0
GISNet: Graph-Based Information Sharing Network For Vehicle Trajectory Prediction—0
GitNet: Geometric Prior-based Transformation for Birds-Eye-View Segmentation—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