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 4751–4800 of 6092 papers

TitleStatusHype
VISTREAM: Improving Computation Efficiency of Visual Streaming Perception via Law-of-Charge-Conservation Inspired Spiking Neural Network—0
Visual Adversarial Attack on Vision-Language Models for Autonomous Driving—0
Visual Analytics of Neuron Vulnerability to Adversarial Attacks on Convolutional Neural Networks—0
Visual Attention for Behavioral Cloning in Autonomous Driving—0
VisualBackProp for learning using privileged information with CNNs—0
Visual Exemplar Driven Task-Prompting for Unified Perception in Autonomous Driving—0
Visual Localization for Autonomous Driving: Mapping the Accurate Location in the City Maze—0
Visual Saliency-Guided Channel Pruning for Deep Visual Detectors in Autonomous Driving—0
Visual Semantic Search: Retrieving Videos via Complex Textual Queries—0
Visual Sensor Pose Optimisation Using Visibility Models for Smart Cities—0
Visual SLAMMOT Considering Multiple Motion Models—0
VLC Fusion: Vision-Language Conditioned Sensor Fusion for Robust Object Detection—0
VLM-AD: End-to-End Autonomous Driving through Vision-Language Model Supervision—0
VLM-Assisted Continual learning for Visual Question Answering in Self-Driving—0
VLM-C4L: Continual Core Dataset Learning with Corner Case Optimization via Vision-Language Models for Autonomous Driving—0
VLM-E2E: Enhancing End-to-End Autonomous Driving with Multimodal Driver Attention Fusion—0
VLMine: Long-Tail Data Mining with Vision Language Models—0
VLM-RL: A Unified Vision Language Models and Reinforcement Learning Framework for Safe Autonomous Driving—0
VLP: Vision Language Planning for Autonomous Driving—0
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
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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