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 3351–3375 of 6092 papers

TitleStatusHype
SparseAD: Sparse Query-Centric Paradigm for Efficient End-to-End Autonomous Driving—0
SparseAlign: A Fully Sparse Framework for Cooperative Object Detection—0
Sparse Depth Completion with Semantic Mesh Deformation Optimization—0
SparseDet: A Simple and Effective Framework for Fully Sparse LiDAR-based 3D Object Detection—0
Sparse Laneformer—0
SparseOcc: Rethinking Sparse Latent Representation for Vision-Based Semantic Occupancy Prediction—0
Sparse Pedestrian Character Learning for Trajectory Prediction—0
Sparse Point Clouds Assisted Learned Image Compression—0
Sparse Points to Dense Clouds: Enhancing 3D Detection with Limited LiDAR Data—0
SparseRadNet: Sparse Perception Neural Network on Subsampled Radar Data—0
Sparse Refinement for Efficient High-Resolution Semantic Segmentation—0
SparseTem: Boosting the Efficiency of CNN-Based Video Encoders by Exploiting Temporal Continuity—0
Sparsity-based Safety Conservatism for Constrained Offline Reinforcement Learning—0
Reinforcement Learning With Sparse-Executing Actions via Sparsity Regularization—0
Spatial-Channel Transformer Network for Trajectory Prediction on the Traffic Scenes—0
Spatial Correspondence With Generative Adversarial Network: Learning Depth From Monocular Videos—0
Spatial Intelligence of a Self-driving Car and Rule-Based Decision Making—0
Spatially and Seamlessly Hierarchical Reinforcement Learning for State Space and Policy space in Autonomous Driving—0
Spatial Reasoning and Planning for Deep Embodied Agents—0
Spatial-SpinDrop: Spatial Dropout-based Binary Bayesian Neural Network with Spintronics Implementation—0
Spatial-Temporal Block and LSTM Network for Pedestrian Trajectories Prediction—0
Spatio-Temporal Gating-Adjacency GCN for Human Motion Prediction—0
Spatio-Contextual Deep Network Based Multimodal Pedestrian Detection For Autonomous Driving—0
Spatio-Temporal Bi-directional Cross-frame Memory for Distractor Filtering Point Cloud Single Object Tracking—0
Spatiotemporal Costmap Inference for MPC via Deep Inverse Reinforcement Learning—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