Self-Driving Cars
Self-driving cars : the task of making a car that can drive itself without human guidance.
State-of-the-art leaderboards
Greatest papers with code
Learning a Driving Simulator
• commaai/research
• 
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.
Fast Algorithms for Convolutional Neural Networks
CVPR 2016
• XiaoMi/mace
•
The algorithms compute minimal complexity convolution over small tiles, which makes them fast with small filters and small batch sizes.
End to End Learning for Self-Driving Cars
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.
PifPaf: Composite Fields for Human Pose Estimation
CVPR 2019
• vita-epfl/openpifpaf
• 
We propose a new bottom-up method for multi-person 2D human pose estimation that is particularly well suited for urban mobility such as self-driving cars and delivery robots.
#4 best model for
Keypoint Detection
on COCO
KEYPOINT DETECTION MULTI-PERSON POSE ESTIMATION SELF-DRIVING CARS
Generating Contrastive Explanations with Monotonic Attribute Functions
In this paper, we propose a method that can generate contrastive explanations for such data where we not only highlight aspects that are in themselves sufficient to justify the classification by the deep model, but also new aspects which if added will change the classification.
Social GAN: Socially Acceptable Trajectories with Generative Adversarial Networks
CVPR 2018
• agrimgupta92/sgan
•
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.
MultiCol-SLAM - A Modular Real-Time Multi-Camera SLAM System
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).
SemanticKITTI: A Dataset for Semantic Scene Understanding of LiDAR Sequences
Despite the relevance of semantic scene understanding for this application, there is a lack of a large dataset for this task which is based on an automotive LiDAR.
On a Formal Model of Safe and Scalable Self-driving Cars
In the second part we describe a design of a system that adheres to our safety assurance requirements and is scalable to millions of cars.
Motion Planning Networks
• ahq1993/MPNet
•
Fast and efficient motion planning algorithms are crucial for many state-of-the-art robotics applications such as self-driving cars.