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 3901–3950 of 6092 papers

TitleStatusHype
VL-SAFE: Vision-Language Guided Safety-Aware Reinforcement Learning with World Models for Autonomous Driving—0
VL-UR: Vision-Language-guided Universal Restoration of Images Degraded by Adverse Weather Conditions—0
VM-MODNet: Vehicle Motion aware Moving Object Detection for Autonomous Driving—0
Voxel-FPN: multi-scale voxel feature aggregation in 3D object detection from point clouds—0
VQA-Diff: Exploiting VQA and Diffusion for Zero-Shot Image-to-3D Vehicle Asset Generation in Autonomous Driving—0
VSO: Visual Semantic Odometry—0
VT-Former: An Exploratory Study on Vehicle Trajectory Prediction for Highway Surveillance through Graph Isomorphism and Transformer—0
VVRec: Reconstruction Attacks on DL-based Volumetric Video Upstreaming via Latent Diffusion Model with Gamma Distribution—0
WAD: A Deep Reinforcement Learning Agent for Urban Autonomous Driving—0
Waymo Open Dataset: Panoramic Video Panoptic Segmentation—0
Weakly Supervised Class-Agnostic Motion Prediction for Autonomous Driving—0
Weakly Supervised Multi-Modal 3D Human Body Pose Estimation for Autonomous Driving—0
Weather and Light Level Classification for Autonomous Driving: Dataset, Baseline and Active Learning—0
Weather Influence and Classification with Automotive Lidar Sensors—0
What Do Adversarially trained Neural Networks Focus: A Fourier Domain-based Study—0
What do we need to build explainable AI systems for the medical domain?—0
What Face and Body Shapes Can Tell About Height—0
What Makes a Place? Building Bespoke Place Dependent Object Detectors for Robotics—0
What Matters to Enhance Traffic Rule Compliance of Imitation Learning for End-to-End Autonomous Driving—0
What Truly Matters in Trajectory Prediction for Autonomous Driving?—0
When Neural Networks Using Different Sensors Create Similar Features—0
When, Where, and What? A Novel Benchmark for Accident Anticipation and Localization with Large Language Models—0
Where to drive: free space detection with one fisheye camera—0
Which to Match? Selecting Consistent GT-Proposal Assignment for Pedestrian Detection—0
Whose Track Is It Anyway? Improving Robustness to Tracking Errors With Affinity-Based Trajectory Prediction—0
Who Walks With You Matters: Perceiving Social Interactions with Groups for Pedestrian Trajectory Prediction—0
Why current rain denoising models fail on CycleGAN created rain images in autonomous driving—0
WildOcc: A Benchmark for Off-Road 3D Semantic Occupancy Prediction—0
A Survey on Large Language Model-empowered Autonomous Driving—0
Windscreen Optical Quality for AI Algorithms: Refractive Power and MTF not Sufficient—0
Winning the ICCV 2019 Learning to Drive Challenge—0
WiseMove: A Framework for Safe Deep Reinforcement Learning for Autonomous Driving—0
Wolf: Captioning Everything with a World Summarization Framework—0
Woodscape Fisheye Object Detection for Autonomous Driving -- CVPR 2022 OmniCV Workshop Challenge—0
Woodscape Fisheye Semantic Segmentation for Autonomous Driving -- CVPR 2021 OmniCV Workshop Challenge—0
WoodScape Motion Segmentation for Autonomous Driving -- CVPR 2023 OmniCV Workshop Challenge—0
Work-in-Progress: Traded Control Transfer for Managing Real-Time Sensor Uncertainties in Autonomous Vehicle—0
World knowledge-enhanced Reasoning Using Instruction-guided Interactor in Autonomous Driving—0
World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving—0
World Models for Autonomous Driving: An Initial Survey—0
WorldSimBench: Towards Video Generation Models as World Simulators—0
WTCL-Dehaze: Rethinking Real-world Image Dehazing via Wavelet Transform and Contrastive Learning—0
WTS: A Pedestrian-Centric Traffic Video Dataset for Fine-grained Spatial-Temporal Understanding—0
X-Align: Cross-Modal Cross-View Alignment for Bird's-Eye-View Segmentation—0
X-Align++: cross-modal cross-view alignment for Bird's-eye-view segmentation—0
X-Driver: Explainable Autonomous Driving with Vision-Language Models—0
XLD: A Cross-Lane Dataset for Benchmarking Novel Driving View Synthesis—0
XLM for Autonomous Driving Systems: A Comprehensive Review—0
X-Scene: Large-Scale Driving Scene Generation with High Fidelity and Flexible Controllability—0
X-view: Non-egocentric Multi-View 3D Object Detector—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