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18551_project

abnormal-behavior-detection

Abnormal behavior detection in the video surveillance based on yolo darknet

atss

Bridging the Gap Between Anchor-based and Anchor-free Detection via Adaptive Training Sample Selection

audacity

开源的音频处理软件

bgslibrary

A Background Subtraction Library

bisenet

mIOU=78.4 on cityscapes. My implementation of paper: BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation

caffe

Caffe: a fast framework for deep learning. For the most recent version checkout the dev branch. For the latest stable release checkout the master branch.

caffe-lstm

LSTM implementation on Caffe

caffe-posenet

Implementation of PoseNet

caffe-tutorial

DIY Deep Learning for Vision: a Hands-On Tutorial with Caffe

caffe-yolo

YOLO (Real-Time Object Detection) in caffe

carc

Cross-Age Reference Coding for Age-Invariant Face Recognition and Retrieval

ccv

C-based/Cached/Core Computer Vision Library, A Modern Computer Vision Library

cf_tracking

C++ Implementation of two correlation filter based visual trackers

circulant_matrix_tracker

Python port of João F. Henriques circulant matrix tracker

clandmark

Open Source Landmarking Library

cmakeexamples

cmake examples for test

cmcode

Ming-Ming Cheng's open source projects

cmt

convnet

A GPU implementation of Convolutional Neural Nets in C++

convnet-benchmarks

Easy benchmarking of all public open-source implementations of convnets

convolutionalrbm.m

A MATLAB / MEX / CUDA-MEX implementation of Convolutional Restricted Boltzmann Machines.

crcn

Coherence + Recurrent Neural Network + Convolutional Neural Network

darkflow

Translate darknet to tensorflow. Load trained weights, retrain/fine-tune using tensorflow, export constant graph def to mobile devices

darknet

Convolutional Neural Network

darknet_mobilenet

mobilenet 与darknet yolo

deepface

基于Caffe实现的深度学习人脸识别、脸脸检测、人脸关键点检测等工作

deeplearningtutorials

Deep Learning Tutorial notes and code. See the wiki for more info.

deeplearntoolbox

Matlab/Octave toolbox for deep learning. Includes Deep Belief Nets, Stacked Autoencoders, Convolutional Neural Nets, Convolutional Autoencoders and vanilla Neural Nets. Each method has examples to get you started.

deepskeleton

:racehorse:code for cvpr2016 paper "Object Skeleton Extraction in Natural Images by Fusing Scale-associated Deep Side Outputs"