Autonomous Vehicles
534 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
Not All Voxels Are Equal: Hardness-Aware Semantic Scene Completion with Self-Distillation
Furthermore, the voxels in the boundary region are more challenging to differentiate than those in the interior.
VBR: A Vision Benchmark in Rome
This paper presents a vision and perception research dataset collected in Rome, featuring RGB data, 3D point clouds, IMU, and GPS data.
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.
