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 1601–1625 of 6092 papers

TitleStatusHype
dAJC: A 2.02mW 50Mbps Direct Analog to MJPEG Converter for Video Sensor Node using Low-Noise Switched Capacitor MAC-Quantizer with Auto-Calibration and Sparsity-Aware ADC—0
Cloud-Edge-Terminal Collaborative AIGC for Autonomous Driving—0
AutoSplat: Constrained Gaussian Splatting for Autonomous Driving Scene Reconstruction—0
FlowTrack: Point-level Flow Network for 3D Single Object Tracking—0
DM3D: Distortion-Minimized Weight Pruning for Lossless 3D Object Detection—0
Research on Reliable and Safe Occupancy Grid Prediction in Underground Parking Lots—0
Uni-DVPS: Unified Model for Depth-Aware Video Panoptic SegmentationCode1
Let Hybrid A* Path Planner Obey Traffic Rules: A Deep Reinforcement Learning-Based Planning Framework—0
Acceleration method for generating perception failure scenarios based on editing Markov process—0
Tokenize the World into Object-level Knowledge to Address Long-tail Events in Autonomous Driving—0
FALCON: Frequency Adjoint Link with CONtinuous Density Mask for Fast Single Image Dehazing—0
SeFlow: A Self-Supervised Scene Flow Method in Autonomous DrivingCode2
Predicting Trust Dynamics with Dynamic SEM in Human-AI Cooperation—0
Deep Reinforcement Learning for Adverse Garage Scenario Generation—0
HGNET: A Hierarchical Feature Guided Network for Occupancy Flow Field Prediction—0
CaFNet: A Confidence-Driven Framework for Radar Camera Depth EstimationCode1
A Rule-Based Behaviour Planner for Autonomous Driving—0
Deep Learning-based Depth Estimation Methods from Monocular Image and Videos: A Comprehensive Survey—0
StreamMOTP: Streaming and Unified Framework for Joint 3D Multi-Object Tracking and Trajectory Prediction—0
BiCo-Fusion: Bidirectional Complementary LiDAR-Camera Fusion for Semantic- and Spatial-Aware 3D Object Detection—0
XLD: A Cross-Lane Dataset for Benchmarking Novel Driving View Synthesis—0
Optimization of Autonomous Driving Image Detection Based on RFAConv and Triplet Attention—0
MDHA: Multi-Scale Deformable Transformer with Hybrid Anchors for Multi-View 3D Object DetectionCode0
Image-Guided Outdoor LiDAR Perception Quality Assessment for Autonomous Driving—0
Querying Labeled Time Series Data with Scenario Programs—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