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Autonomous Driving

132 papers with code ยท Computer Vision
Subtask of Autonomous Vehicles

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.

State-of-the-art leaderboards

You can find evaluation results in the subtasks. You can also submitting evaluation metrics for this task.

Latest papers without code

On learning visual odometry errors

ICLR 2020

This paper fosters the idea that deep learning methods can be sided to classical visual odometry pipelines to improve their accuracy and to produce uncertainty models to their estimations.

AUTONOMOUS DRIVING VISUAL ODOMETRY

Variational Constrained Reinforcement Learning with Application to Planning at Roundabout

ICLR 2020

In this paper, we combine variational learning and constrained reinforcement learning to simultaneously learn a Conditional Representation Model (CRM) to encode the states into safe and unsafe distributions respectively as well as to learn the corresponding safe policy.

AUTONOMOUS DRIVING

Efficacy of Pixel-Level OOD Detection for Semantic Segmentation

ICLR 2020

The detection of out of distribution samples for image classification has been widely researched.

AUTONOMOUS DRIVING IMAGE CLASSIFICATION SEMANTIC SEGMENTATION

A Survey of Deep Learning Techniques for Autonomous Driving

17 Oct 2019

The last decade witnessed increasingly rapid progress in self-driving vehicle technology, mainly backed up by advances in the area of deep learning and artificial intelligence.

AUTONOMOUS DRIVING

Depth Completion from Sparse LiDAR Data with Depth-Normal Constraints

15 Oct 2019

Most of existing methods directly train a network to learn a mapping from sparse depth inputs to dense depth maps, which has difficulties in utilizing the 3D geometric constraints and handling the practical sensor noises.

AUTONOMOUS DRIVING DEPTH COMPLETION

ICPS-net: An End-to-End RGB-based Indoor Camera Positioning System using deep convolutional neural networks

14 Oct 2019

Indoor positioning and navigation inside an area with no GPS-data availability is a challenging problem.

AUTONOMOUS DRIVING

Federated Transfer Reinforcement Learning for Autonomous Driving

14 Oct 2019

Reinforcement learning (RL) is widely used in autonomous driving tasks and training RL models typically involves in a multi-step process: pre-training RL models on simulators, uploading the pre-trained model to real-life robots, and fine-tuning the weight parameters on robot vehicles.

AUTONOMOUS DRIVING TRANSFER REINFORCEMENT LEARNING

FuseMODNet: Real-Time Camera and LiDAR based Moving Object Detection for robust low-light Autonomous Driving

11 Oct 2019

In this work, we propose a robust and real-time CNN architecture for Moving Object Detection (MOD) under low-light conditions by capturing motion information from both camera and LiDAR sensors.

AUTONOMOUS DRIVING OBJECT DETECTION OPTICAL FLOW ESTIMATION

Autonomous Driving using Safe Reinforcement Learning by Incorporating a Regret-based Human Lane-Changing Decision Model

10 Oct 2019

The predicted decisions are incorporated in the safety constraints for reinforcement learning in training and in implementation.

AUTONOMOUS DRIVING DECISION MAKING