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adversarial-frcnn

A-Fast-RCNN (CVPR 2017)

caffe-faster-rcnn

faster rcnn c++ version. joint train; please checkout into dev branch (git checkout dev)

caffe-yolo

YOLO (Real-Time Object Detection) in caffe

caffe-yolo9000

Caffe for YOLOv2 & YOLO9000

chainer-simple-fast-rnn

Chainer's simple implementation of fast R-CNN

darkflow

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

darknet

Convolutional Neural Networks

darknet_scripts

Auxilary scripts to work with (YOLO) darknet deep learning famework. AKA -> How to generate YOLO anchors?

deeplearn

Implementation of research papers on Deep Learning+ NLP+ CV in Python using Keras, Tensorflow and Scikit Learn.

deformable-convnets

Deformable Convolutional Networks

dgcnn

donkey

self driving car

elf

ELF: a platform for game research

fashion-detection

Fashion Detection in the Wild (Deep Clothes Detector)

fashion-landmarks

Fashion Landmark Detection in the Wild

fast-rcnn

Fast R-CNN

fast-rcnn-torch

Fast R-CNN Torch Implementation

faster-rcnn.pytorch

A faster pytorch implementation of faster r-cnn

faster-rcnn_tf

Faster-RCNN in Tensorflow

faster_rcnn

Faster R-CNN

keras-frcnn

keras-yolo3

Training and Detecting Objects with YOLO3

lightnet

🌓 Bringing pjreddie's DarkNet out of the shadows #yolo

mobilenet-ssd

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

munit

Multimodal Unsupervised Image-to-Image Translation

mx-rcnn

Parallel Faster R-CNN implementation with MXNet.

mxnet-ssd

MXNet port of SSD: Single Shot MultiBox Object Detector. Reimplementation of https://github.com/weiliu89/caffe/tree/ssd

nvvl

A library that uses hardware acceleration to load sequences of video frames to facilitate machine learning training

openlabeling

Open Source labeling tool to generate the training data in the format YOLO requires.

progressive_growing_of_gans

Progressive Growing of GANs for Improved Quality, Stability, and Variation