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 3551–3575 of 6092 papers

TitleStatusHype
CORT: Class-Oriented Real-time Tracking for Embedded Systems—0
CoSEC: A Coaxial Stereo Event Camera Dataset for Autonomous Driving—0
CoT-Drive: Efficient Motion Forecasting for Autonomous Driving with LLMs and Chain-of-Thought Prompting—0
Co-Teaching: An Ark to Unsupervised Stereo Matching—0
Coupled Distributional Random Expert Distillation for World Model Online Imitation Learning—0
Coverage-based Scene Fuzzing for Virtual Autonomous Driving Testing—0
Coverage Testing of Deep Learning Models using Dataset Characterization—0
CoVLA: Comprehensive Vision-Language-Action Dataset for Autonomous Driving—0
CP-Guard+: A New Paradigm for Malicious Agent Detection and Defense in Collaborative Perception—0
CP-Guard: Malicious Agent Detection and Defense in Collaborative Bird's Eye View Perception—0
CP-loss: Connectivity-preserving Loss for Road Curb Detection in Autonomous Driving with Aerial Images—0
CP-NCBF: A Conformal Prediction-based Approach to Synthesize Verified Neural Control Barrier Functions—0
CPSeg: Cluster-free Panoptic Segmentation of 3D LiDAR Point Clouds—0
CramNet: Camera-Radar Fusion with Ray-Constrained Cross-Attention for Robust 3D Object Detection—0
CrashAgent: Crash Scenario Generation via Multi-modal Reasoning—0
CRASH: Crash Recognition and Anticipation System Harnessing with Context-Aware and Temporal Focus Attentions—0
Critic-V: VLM Critics Help Catch VLM Errors in Multimodal Reasoning—0
CRKD: Enhanced Camera-Radar Object Detection with Cross-modality Knowledge Distillation—0
CRLLK: Constrained Reinforcement Learning for Lane Keeping in Autonomous Driving—0
Cross-Cluster Shifting for Efficient and Effective 3D Object Detection in Autonomous Driving—0
Cross-Dataset Collaborative Learning for Semantic Segmentation in Autonomous Driving—0
Cross-Domain Car Detection Model with Integrated Convolutional Block Attention Mechanism—0
Cross-domain Federated Object Detection—0
Cross-domain Few-shot In-context Learning for Enhancing Traffic Sign Recognition—0
Cross-Enhancement Transform Two-Stream 3D ConvNets for Action Recognition—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