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

Showing 14011425 of 6092 papers

TitleStatusHype
xMUDA: Cross-Modal Unsupervised Domain Adaptation for 3D Semantic SegmentationCode1
Multi-source Domain Adaptation for Semantic SegmentationCode1
CityLearn: Diverse Real-World Environments for Sample-Efficient Navigation Policy LearningCode1
Development of a hand pose recognition system on an embedded computer using Artificial IntelligenceCode1
PIE: A Large-Scale Dataset and Models for Pedestrian Intention Estimation and Trajectory PredictionCode1
Talk2Car: Taking Control of Your Self-Driving CarCode1
SalsaNet: Fast Road and Vehicle Segmentation in LiDAR Point Clouds for Autonomous DrivingCode1
Cooperation-Aware Lane Change Maneuver in Dense Traffic based on Model Predictive Control with Recurrent Neural NetworkCode1
GRIP++: Enhanced Graph-based Interaction-aware Trajectory Prediction for Autonomous DrivingCode1
M3D-RPN: Monocular 3D Region Proposal Network for Object DetectionCode1
Instance Segmentation by Jointly Optimizing Spatial Embeddings and Clustering BandwidthCode1
Fooling Detection Alone is Not Enough: First Adversarial Attack against Multiple Object TrackingCode1
Precise Synthetic Image and LiDAR (PreSIL) Dataset for Autonomous Vehicle PerceptionCode1
Dynamic Environment Prediction in Urban Scenes using Recurrent Representation LearningCode1
Model-free Deep Reinforcement Learning for Urban Autonomous DrivingCode1
Group-wise Correlation Stereo NetworkCode1
Unsupervised Traffic Accident Detection in First-Person VideosCode1
PIXOR: Real-time 3D Object Detection from Point CloudsCode1
A Curriculum Domain Adaptation Approach to the Semantic Segmentation of Urban ScenesCode1
Pseudo-LiDAR from Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous DrivingCode1
Egocentric Vision-based Future Vehicle Localization for Intelligent Driving Assistance SystemsCode1
Guiding Deep Learning System Testing using Surprise AdequacyCode1
BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask LearningCode1
The ApolloScape Open Dataset for Autonomous Driving and its ApplicationCode1
Predicting Driver Attention in Critical SituationsCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ReasonNetDriving Score79.95Unverified
2InterFuserDriving Score76.18Unverified
3TCPDriving Score75.14Unverified
4TF++ WPDriving Score66.32Unverified
5Learning From All Vehicles (LAV)Driving Score61.85Unverified
6TransFuserDriving Score61.18Unverified
7TransFuser (Reproduced)Driving Score55.04Unverified
8TCP (Reproduced)Driving Score47.91Unverified
9Latent TransFuserDriving Score45.2Unverified
10GRIADDriving Score36.79Unverified
#ModelMetricClaimedVerifiedStatus
1Geometric FusionRC69.17Unverified
2TransFuserRC56.36Unverified
#ModelMetricClaimedVerifiedStatus
1Geometric FusionRC86.91Unverified
2TransFuserRC78.41Unverified