Self-Driving Cars

93 papers with code • 0 benchmarks • 11 datasets

Self-driving cars : the task of making a car that can drive itself without human guidance.

( Image credit: Learning a Driving Simulator )

Greatest papers with code

Fast Algorithms for Convolutional Neural Networks

XiaoMi/mace CVPR 2016

The algorithms compute minimal complexity convolution over small tiles, which makes them fast with small filters and small batch sizes.

Pedestrian Detection Self-Driving Cars

Learning a Driving Simulator

commaai/research 3 Aug 2016

Comma. ai's approach to Artificial Intelligence for self-driving cars is based on an agent that learns to clone driver behaviors and plans maneuvers by simulating future events in the road.

Self-Driving Cars Video Prediction

End to End Learning for Self-Driving Cars

marsauto/europilot 25 Apr 2016

The system automatically learns internal representations of the necessary processing steps such as detecting useful road features with only the human steering angle as the training signal.

Lane Detection Self-Driving Cars

Leveraging Latent Features for Local Explanations

Trusted-AI/AIX360 29 May 2019

As the application of deep neural networks proliferates in numerous areas such as medical imaging, video surveillance, and self driving cars, the need for explaining the decisions of these models has become a hot research topic, both at the global and local level.

General Classification Self-Driving Cars

OpenPifPaf: Composite Fields for Semantic Keypoint Detection and Spatio-Temporal Association

vita-epfl/openpifpaf 3 Mar 2021

We present a generic neural network architecture that uses Composite Fields to detect and construct a spatio-temporal pose which is a single, connected graph whose nodes are the semantic keypoints (e. g., a person's body joints) in multiple frames.

Keypoint Detection Multi-Person Pose Estimation +1

Sparse Auxiliary Networks for Unified Monocular Depth Prediction and Completion

TRI-ML/packnet-sfm CVPR 2021

Estimating scene geometry from data obtained with cost-effective sensors is key for robots and self-driving cars.

Depth Estimation Self-Driving Cars

Social GAN: Socially Acceptable Trajectories with Generative Adversarial Networks

agrimgupta92/sgan CVPR 2018

Understanding human motion behavior is critical for autonomous moving platforms (like self-driving cars and social robots) if they are to navigate human-centric environments.

Motion Forecasting Multi-future Trajectory Prediction +2

MultiCol-SLAM - A Modular Real-Time Multi-Camera SLAM System

urbste/MultiCol-SLAM 24 Oct 2016

The basis for most vision based applications like robotics, self-driving cars and potentially augmented and virtual reality is a robust, continuous estimation of the position and orientation of a camera system w. r. t the observed environment (scene).

Self-Driving Cars Simultaneous Localization and Mapping +1