Top 281 caffe open source projects

Compact Generalized Non-local Network (NIPS 2018)

A review of change detection methods, including codes and open data sets for deep learning. From paper: change detection based on artificial intelligence: state-of-the-art and challenges.

Implementation based on the paper Li et al., “A Convolutional Neural Network Cascade for Face Detection, ” 2015 CVPR

Squeeze-and-Excitation Networks

The Convolutional Neural Network(CNN) for Android

Simple implementation of kpzhang93's paper from Matlab to c++, and don't change models.

Reimplement RetinaFace use C++ and TensorRT

Automatic colorization using deep neural networks. "Colorful Image Colorization." In ECCV, 2016.

Caffe for Sparse Convolutional Neural Network

Domain Guided Dropout for Person Re-identification

Caffe2 on iOS Real-time Demo. Test with Your Own Model and Photos.

ID-discriminative Embedding (IDE) for Person Re-identification

A windows caffe implementation of YOLO detection network

通用深度学习推理服务，可在生产环境中快速上线由TensorFlow、PyTorch、Caffe框架训练出的深度学习模型。

Deep learning software for colorizing black and white images with a few clicks.

Oriented Response Networks, in CVPR 2017

Supervised Semantics-preserving Deep Hashing (TPAMI18)

Weakly-Supervised Semantic Segmentation Network with Deep Seeded Region Growing (CVPR 2018).

Visualizer for neural network, deep learning, and machine learning models

MTCNN with Motion Detection, on Raspberry Pi with Love

MTCNN Face Detection & Alignment

Auto-ReID and Other Person Re-Identification Projects

Automatic image captioning model based on Caffe, using features from bottom-up attention.

A Lightweight Optical Flow CNN - Revisiting Data Fidelity and Regularization, TPAMI 2020

The repository contains source code and models to use PixelNet architecture used for various pixel-level tasks. More details can be accessed at <http://www.cs.cmu.edu/~aayushb/pixelNet/>.

php wrapper for opencv

Deep Learning API and Server in C++14 support for Caffe, Caffe2, PyTorch,TensorRT, Dlib, NCNN, Tensorflow, XGBoost and TSNE

Collective Knowledge workflow for Caffe to automate installation across diverse platforms and to collaboratively evaluate and optimize Caffe-based workloads across diverse hardware, software and data sets (compilers, libraries, tools, models, inputs):

Light field video applications (e.g. video refocusing, focus tracking, changing aperture and view)

Toolbox for converting analog to spiking neural networks (ANN to SNN), and running them in a spiking neuron simulator.

Use caffe to train your own data in just one click

Data Augmentation for Caffe

Caffe implementation for "Hidden Two-Stream Convolutional Networks for Action Recognition"

Video-friendly caffe -- comes with the most recent version of Caffe (as of Jan 2019), a video reader, 3D(ND) pooling layer, and an example training script for C3D network and UCF-101 data

A Caffe Re-Implementation of SENet

This repository was a fork of BVLC/caffe and includes the upsample, bn, dense_image_data and softmax_with_loss (with class weighting) layers of caffe-segnet (https://github.com/alexgkendall/caffe-segnet) to run SegNet with cuDNN version 5.

Deformable Convolutional Networks on caffe

The NNEF Tools repository contains tools to generate and consume NNEF documents

Caffe for YOLOv2 & YOLO9000

ResNet-20/32/44/56/110 on CIFAR-10 with Caffe

code for py-R-FCN-multiGPU maintained by bupt-priv

SphereFace+ Implementation for <Learning towards Minimum Hyperspherical Energy> in NIPS'18.

pytorch 2 caffe

Türkiye'de yapılan derin öğrenme (deep learning) ve makine öğrenmesi (machine learning) çalışmalarının derlendiği sayfa.

A caffe implementation of mobilenet's depthwise convolution layer.

ncnn is a high-performance neural network inference framework optimized for the mobile platform

Fine-grained classification via second order statistics in a compact end-to-end trainable model

Caffe implementation of Google MobileNet SSD detection network, with pretrained weights on VOC0712 and mAP=0.727.

Real-World Anomaly Detection in Surveillance Videos

Split-Brain Autoencoders: Unsupervised Learning by Cross-Channel Prediction. In CVPR, 2017.

Dockerfile and runscripts for FlowNet 2.0 (estimation of optical flow)

This is an implematation project of face detection and recognition. The face detection using MTCNN algorithm, and recognition using LightenenCNN algorithm.

AI on Hadoop

Noise-Tolerant Paradigm for Training Face Recognition CNNs

📹 一个短视频APP视频内容安全审核的思路调研及实现汇总

Convert darknet weights to caffemodel

SeqFace : Making full use of sequence information for face recognition

Reimplementation ResNet on cifar10 with caffe

Trojan Attack on Neural Network