SOTAVerified

Autonomous Vehicles

Autonomous vehicles is the task of making a vehicle that can guide itself 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: GSNet: Joint Vehicle Pose and Shape Reconstruction with Geometrical and Scene-aware Supervision )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 691–700 of 2605 papers

TitleStatusHype
Adaptive Splitting of Reusable Temporal Monitors for Rare Traffic ViolationsCode0
Unleashing the True Power of Age-of-Information: Service Aggregation in Connected and Autonomous Vehicles—0
MonoOcc: Digging into Monocular Semantic Occupancy PredictionCode2
Real-time 3D semantic occupancy prediction for autonomous vehicles using memory-efficient sparse convolution—0
Optimized Detection and Classification on GTRSB: Advancing Traffic Sign Recognition with Convolutional Neural Networks—0
MergeOcc: Bridge the Domain Gap between Different LiDARs for Robust Occupancy Prediction—0
Open-World Semantic Segmentation Including Class SimilarityCode2
People Attribute Purpose to Autonomous Vehicles When Explaining Their Behavior: Insights from Cognitive Science for Explainable AICode0
Fine-Grained Pillar Feature Encoding Via Spatio-Temporal Virtual Grid for 3D Object DetectionCode1
Towards Generalizable and Interpretable Motion Prediction: A Deep Variational Bayes Approach—0
Show:102550
← PrevPage 70 of 261Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1BAAMA3DP22.85—Unverified
2GSNetA3DP20.21—Unverified