Autonomous Driving
1421 papers with code • 4 benchmarks • 66 datasets
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)
Libraries
Use these libraries to find Autonomous Driving models and implementationsDatasets
Latest papers
SEVD: Synthetic Event-based Vision Dataset for Ego and Fixed Traffic Perception
In response to this gap, we present SEVD, a first-of-its-kind multi-view ego, and fixed perception synthetic event-based dataset using multiple dynamic vision sensors within the CARLA simulator.
WROOM: An Autonomous Driving Approach for Off-Road Navigation
Off-road navigation is a challenging problem both at the planning level to get a smooth trajectory and at the control level to avoid flipping over, hitting obstacles, or getting stuck at a rough patch.
PASA: Attack Agnostic Unsupervised Adversarial Detection using Prediction & Attribution Sensitivity Analysis
However, we observe that both model predictions and feature attributions for input samples are sensitive to noise.
PillarTrack: Redesigning Pillar-based Transformer Network for Single Object Tracking on Point Clouds
LiDAR-based 3D single object tracking (3D SOT) is a critical issue in robotics and autonomous driving.
Can Vehicle Motion Planning Generalize to Realistic Long-tail Scenarios?
We assess existing state-of-the-art planners on our benchmark and show that neither rule-based nor learning-based planners can safely navigate the interPlan scenarios.
Homography Guided Temporal Fusion for Road Line and Marking Segmentation
Reliable segmentation of road lines and markings is critical to autonomous driving.
NeuroNCAP: Photorealistic Closed-loop Safety Testing for Autonomous Driving
We present a versatile NeRF-based simulator for testing autonomous driving (AD) software systems, designed with a focus on sensor-realistic closed-loop evaluation and the creation of safety-critical scenarios.
Scaling Multi-Camera 3D Object Detection through Weak-to-Strong Eliciting
Finally, for MC3D-Det joint training, the elaborate dataset merge strategy is designed to solve the problem of inconsistent camera numbers and camera parameters.
RoadBEV: Road Surface Reconstruction in Bird's Eye View
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.
HPNet: Dynamic Trajectory Forecasting with Historical Prediction Attention
The proposed Historical Prediction Attention together with the Agent Attention and Mode Attention is further formulated as the Triple Factorized Attention module, serving as the core design of HPNet. Experiments on the Argoverse and INTERACTION datasets show that HPNet achieves state-of-the-art performance, and generates accurate and stable future trajectories.