| spacejack/carphysics2d |
121 |
|
0 |
0 |
over 6 years ago |
0 |
|
0 |
mit |
JavaScript |
| Simple 2D car physics |
| wlwkgus/DeepSpectralClustering |
77 |
|
0 |
0 |
over 7 years ago |
0 |
|
2 |
|
Python |
| Pytorch Implemention of paper "Deep Spectral Clustering Learning", the state of the art of the Deep Metric Learning Paper |
| Epiphqny/Multiple-instance-learning |
56 |
|
0 |
0 |
over 6 years ago |
0 |
|
3 |
|
Python |
| Pytorch implementation of three Multiple Instance Learning or Multi-classification papers |
| abhinavsagar/self-driving-car |
46 |
|
0 |
0 |
almost 5 years ago |
0 |
|
1 |
mit |
Jupyter Notebook |
| Implementation of the paper "End to End Learning for Self-Driving Cars" |
| JackEasson/SLPNet_pytorch |
41 |
|
0 |
0 |
over 3 years ago |
0 |
|
6 |
|
Python |
| SLPNet: Towards End-to-End Car License Plates Detection and Recognition Using Lightweight CNN |
| aniskoubaa/car_detection_yolo_faster_rcnn_uvsc2019 |
39 |
|
0 |
0 |
about 7 years ago |
0 |
|
1 |
|
Python |
| This repo contains all the source code and dataset used in the paper Car Detection using Unmanned Aerial Vehicles: Comparison between Faster R-CNN and YOLOv3 |
| asheshjain399/ICCV2015_Brain4Cars |
38 |
|
0 |
0 |
almost 10 years ago |
0 |
|
1 |
other |
Matlab |
| Code for ICCV2015 paper "Car That Knows Before You Do: Anticipating Maneuvers via Learning Temporal Driving Models" |
| morganmcg1/stanford-cars |
31 |
|
0 |
0 |
about 6 years ago |
0 |
|
1 |
apache-2.0 |
Jupyter Notebook |
| Learning computer vision by striving to maximise accuracy on the Stanford Cars dataset |
| autonomousvision/texture_fields |
29 |
|
0 |
0 |
about 6 years ago |
0 |
|
0 |
mit |
Python |
| This repository contains code for the paper 'Texture Fields: Learning Texture Representations in Function Space'. |
| ermolenkodev/keras-salient-object-visualisation |
28 |
|
0 |
0 |
over 4 years ago |
0 |
|
0 |
apache-2.0 |
Jupyter Notebook |
| Keras implementation of nvidia paper 'Explaining How a Deep Neural Network Trained with End-to-End Learning Steers a Car'. |