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ciky奇's Projects

cocoapi icon cocoapi

COCO API - Dataset @ http://cocodataset.org/

cv-tricks.com icon cv-tricks.com

Repository for all the tutorials and codes shared at cv-tricks.com

deep_sort icon deep_sort

Simple Online Realtime Tracking with a Deep Association Metric

deeplearning-500-questions icon deeplearning-500-questions

深度学习500问,以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述,以帮助自己及有需要的读者。 全书分为18个章节,近30万字。由于水平有限,书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作,联系[email protected] 版权所有,违权必究 Tan 2018.06

deeppose_tf icon deeppose_tf

DeepPose implementation on TensorFlow. Original Paper http://arxiv.org/abs/1312.4659

detectandtrack icon detectandtrack

The implementation of an algorithm presented in the CVPR18 paper: "Detect-and-Track: Efficient Pose Estimation in Videos"

detectron icon detectron

FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet.

detectron.pytorch icon detectron.pytorch

A pytorch implementation of Detectron. Both training from scratch and inferring directly from pretrained Detectron weights are available.

drbox icon drbox

A deep learning based algorithm to detect rotated object, for example, objects in remote sensing images

extremenet icon extremenet

Bottom-up Object Detection by Grouping Extreme and Center Points

eyewarning icon eyewarning

Android Based Drowsy Driver Detection Application

face-detection-1 icon face-detection-1

Android Mobile Vision API içinde barınan Yüz Tanıma (Face Detection) özelliği ile ilgili örnek bir Android uygulama

face3d icon face3d

Python tools for 3D face: 3DMM, Mesh processing(transform, camera, light, render), 3D face representations.

falldetection icon falldetection

Development of a Fall Detection System, whose main objective is to alert when a person’s fall occurs. The system feature detection sensors (inbuilt mobile sensors) that can detect between normal activities such as running, walking, jumping and an actual fall. By continuously measuring the movement patterns in all directions, the system can compare what it senses to what it considers an actual fall. For this project, we used Android language, and the output of our project is an Android application.

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