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 4851–4875 of 6092 papers

TitleStatusHype
Pixel and Feature Level Based Domain Adaption for Object Detection in Autonomous Driving—0
Pixel-Level Clustering Network for Unsupervised Image Segmentation—0
PixSelect: Less but Reliable Pixels for Accurate and Efficient Localization—0
PixSet : An Opportunity for 3D Computer Vision to Go Beyond Point Clouds With a Full-Waveform LiDAR Dataset—0
PKRD-CoT: A Unified Chain-of-thought Prompting for Multi-Modal Large Language Models in Autonomous Driving—0
Planning and Tracking Control of Full Drive-by-Wire Electric Vehicles in Unstructured Scenario—0
Planning-Aware Diffusion Networks for Enhanced Motion Forecasting in Autonomous Driving—0
Planning with Adaptive World Models for Autonomous Driving—0
Plan-R1: Safe and Feasible Trajectory Planning as Language Modeling—0
Plants Don't Walk on the Street: Common-Sense Reasoning for Reliable Semantic Segmentation—0
PLATYPUS: Progressive Local Surface Estimator for Arbitrary-Scale Point Cloud Upsampling—0
Plausible Uncertainties for Human Pose Regression—0
PLIN: A Network for Pseudo-LiDAR Point Cloud Interpolation—0
PLOP: Probabilistic poLynomial Objects trajectory Planning for autonomous driving—0
PLT-D3: A High-fidelity Dynamic Driving Simulation Dataset for Stereo Depth and Scene Flow—0
PointAugmenting: Cross-Modal Augmentation for 3D Object Detection—0
PointCert: Point Cloud Classification with Deterministic Certified Robustness Guarantees—0
Point Cloud-Assisted Neural Image Compression—0
Point Cloud Based Scene Segmentation: A Survey—0
Point Cloud Compression and Objective Quality Assessment: A Survey—0
PointDifformer: Robust Point Cloud Registration With Neural Diffusion and Transformer—0
PointDP: Diffusion-driven Purification against Adversarial Attacks on 3D Point Cloud Recognition—0
PointeNet: A Lightweight Framework for Effective and Efficient Point Cloud Analysis—0
PointGuard: Provably Robust 3D Point Cloud Classification—0
PointRGCN: Graph Convolution Networks for 3D Vehicles Detection Refinement—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