Self-Driving Cars
169 papers with code • 0 benchmarks • 15 datasets
Self-driving cars : the task of making a car that can drive itself without human guidance.
( Image credit: Learning a Driving Simulator )
Benchmarks
These leaderboards are used to track progress in Self-Driving Cars
Libraries
Use these libraries to find Self-Driving Cars models and implementations
DDAD
Lost and Found
Shifts
Talk2Car
BDD-X
Argoverse 2 Motion Forecasting
SOD
HPD
OC
ELAS
Latest papers with no code
Spiking CenterNet: A Distillation-boosted Spiking Neural Network for Object Detection
To the best of our knowledge, our work is the first approach that takes advantage of knowledge distillation in the field of spiking object detection.
Cross-Layer Performance Evaluation of C-V2X
As self-driving cars increasingly penetrate our daily lives, vehicle-to-everything (V2X) communications are emerging as one of the key enabler technologies.
Enhancing Surveillance Camera FOV Quality via Semantic Line Detection and Classification with Deep Hough Transform
The quality of recorded videos and images is significantly influenced by the camera's field of view (FOV).
DME-Driver: Integrating Human Decision Logic and 3D Scene Perception in Autonomous Driving
On the other hand, the generation of accurate control signals relies on precise and detailed environmental perception, which is where 3D scene perception models excel.
Traffic Sign Recognition Using Local Vision Transformer
The experimental evaluations demonstrate that the hybrid network with the locality module outperforms pure transformer-based models and some of the best convolutional networks in accuracy.
LaksNet: an end-to-end deep learning model for self-driving cars in Udacity simulator
The majority of road accidents occur because of human errors, including distraction, recklessness, and drunken driving.
F$^2$AT: Feature-Focusing Adversarial Training via Disentanglement of Natural and Perturbed Patterns
We propose a Feature-Focusing Adversarial Training (F$^2$AT), which differs from previous work in that it enforces the model to focus on the core features from natural patterns and reduce the impact of spurious features from perturbed patterns.
Fully Sparse Long Range 3D Object Detection Using Range Experts and Multimodal Virtual Points
3D object detection at long-range is crucial for ensuring the safety and efficiency of self-driving cars, allowing them to accurately perceive and react to objects, obstacles, and potential hazards from a distance.
CPIPS: Learning to Preserve Perceptual Distances in End-to-End Image Compression
Lossy image coding standards such as JPEG and MPEG have successfully achieved high compression rates for human consumption of multimedia data.
Gray-box Adversarial Attack of Deep Reinforcement Learning-based Trading Agents
In this research, we demonstrate that a "gray-box" approach for attacking a Deep RL-based trading agent is possible by trading in the same stock market, with no extra access to the trading agent.
