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 2076–2100 of 6092 papers

TitleStatusHype
People Attribute Purpose to Autonomous Vehicles When Explaining Their Behavior: Insights from Cognitive Science for Explainable AICode0
PCLD: Point Cloud Layerwise Diffusion for Adversarial PurificationCode0
DriveDreamer-2: LLM-Enhanced World Models for Diverse Driving Video GenerationCode3
SeSame: Simple, Easy 3D Object Detection with Point-Wise SemanticsCode1
On depth prediction for autonomous driving using self-supervised learning—0
Cross-Cluster Shifting for Efficient and Effective 3D Object Detection in Autonomous Driving—0
SAFDNet: A Simple and Effective Network for Fully Sparse 3D Object DetectionCode2
Fast Kernel Scene FlowCode1
Lightning NeRF: Efficient Hybrid Scene Representation for Autonomous DrivingCode2
JointMotion: Joint Self-Supervision for Joint Motion Prediction—0
LanePtrNet: Revisiting Lane Detection as Point Voting and Grouping on Curves—0
LVIC: Multi-modality segmentation by Lifting Visual Info as Cue—0
OccFusion: Depth Estimation Free Multi-sensor Fusion for 3D Occupancy Prediction—0
DyRoNet: Dynamic Routing and Low-Rank Adapters for Autonomous Driving Streaming Perception—0
FriendNet: Detection-Friendly Dehazing NetworkCode1
Embodied Understanding of Driving ScenariosCode3
LitSim: A Conflict-aware Policy for Long-term Interactive Traffic Simulation—0
Towards learning-based planning:The nuPlan benchmark for real-world autonomous driving—0
Generalizing Cooperative Eco-driving via Multi-residual Task Learning—0
Fooling Neural Networks for Motion Forecasting via Adversarial Attacks—0
Levels of AI Agents: from Rules to Large Language Models—0
Multi-Object Tracking with Camera-LiDAR Fusion for Autonomous Driving—0
Learning Adversarial MDPs with Stochastic Hard Constraints—0
3D Object Visibility Prediction in Autonomous Driving—0
Multi-task Learning for Real-time Autonomous Driving Leveraging Task-adaptive Attention Generator—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