Autonomous Vehicles
531 papers with code • 1 benchmarks • 27 datasets
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 )
Benchmarks
These leaderboards are used to track progress in Autonomous Vehicles
| Trend | Dataset | Best Model | Paper | Code | Compare |
|---|---|---|---|---|---|
|
Libraries
Use these libraries to find Autonomous Vehicles models and implementationsDatasets
CARLA
AirSim
INTERACTION Dataset
Talk2Car
RadarScenes
ROAD
Drive&Act
ApolloCar3D
Argoverse 2 Motion Forecasting
DADA-2000
Subtasks
Latest papers
Enhancing Safety in Mixed Traffic: Learning-Based Modeling and Efficient Control of Autonomous and Human-Driven Vehicles
By incorporating a sparse GP technique in HV modeling and adopting a dynamic GP prediction within the MPC framework, we significantly reduced the computation time of GP-MPC, marking it only 4. 6% higher than that of the conventional MPC.
RoadBEV: Road Surface Reconstruction in Bird's Eye View
ztsrxh/roadbev
•
•
This paper uniformly proposes two simple yet effective models for road elevation reconstruction in BEV named RoadBEV-mono and RoadBEV-stereo, which estimate road elevation with monocular and stereo images, respectively.
DPFT: Dual Perspective Fusion Transformer for Camera-Radar-based Object Detection
tumftm/dpft
•
•
However, cameras are not robust against severe weather conditions, lidar sensors are expensive, and the performance of radar-based perception is still inferior to the others.
Boosting Visual Recognition for Autonomous Driving in Real-world Degradations with Deep Channel Prior
liyuhang166/deep_channel_prior
•
•
The environmental perception of autonomous vehicles in normal conditions have achieved considerable success in the past decade.
Human-compatible driving partners through data-regularized self-play reinforcement learning
Therefore, incorporating realistic human agents is essential for scalable training and evaluation of autonomous driving systems in simulation.
Proprioception Is All You Need: Terrain Classification for Boreal Forests
We show that the combination of two TC datasets yields a latent space that can be interpreted with the properties of the terrains.
Scaling Diffusion Models to Real-World 3D LiDAR Scene Completion
prbonn/lidiff
•
•
Our experimental evaluation shows that our method can complete the scene given a single LiDAR scan as input, producing a scene with more details compared to state-of-the-art scene completion methods.
SmartRefine: A Scenario-Adaptive Refinement Framework for Efficient Motion Prediction
Context information, such as road maps and surrounding agents' states, provides crucial geometric and semantic information for motion behavior prediction.
Belief Aided Navigation using Bayesian Reinforcement Learning for Avoiding Humans in Blind Spots
JinnnK/BNBRLplus
•
•
Recent research on mobile robot navigation has focused on socially aware navigation in crowded environments.
PreSight: Enhancing Autonomous Vehicle Perception with City-Scale NeRF Priors
Autonomous vehicles rely extensively on perception systems to navigate and interpret their surroundings.
