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2021-cv-surveys icon 2021-cv-surveys

2021 年,计算机视觉相关综述。包括目标检测、跟踪........

awesome-object-detection icon awesome-object-detection

Awesome Object Detection based on handong1587 github: https://handong1587.github.io/deep_learning/2015/10/09/object-detection.html

caffe icon caffe

Caffe: a fast open framework for deep learning.

caffe-1 icon caffe-1

This fork of BVLC/Caffe is dedicated to improving performance of this deep learning framework when running on CPU, in particular Intel® Xeon processors (HSW+) and Intel® Xeon Phi processors

caffe-faster-rcnn icon caffe-faster-rcnn

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

cascade-rcnn icon cascade-rcnn

Caffe implementation of multiple popular object detection frameworks

centernet icon centernet

Object detection, 3D detection, and pose estimation using center point detection:

centertrack icon centertrack

Simultaneous object detection and tracking using center points.

cpp_new_features icon cpp_new_features

2021年最新整理, C++ 学习资料,含C++ 11 / 14 / 17 / 20 / 23 新特性、入门教程、推荐书籍、优质文章、学习笔记、教学视频等

cpp_primer_practice icon cpp_primer_practice

搞定C++:punch:。C++ Primer 中文版第5版学习仓库,包括笔记和课后练习答案。

crnn-pytorch icon crnn-pytorch

Pytorch implementation of CRNN (CNN + RNN + CTCLoss) for all language OCR.

d2l-pytorch icon d2l-pytorch

This project reproduces the book Dive Into Deep Learning (www.d2l.ai), adapting the code from MXNet into PyTorch.

db icon db

A PyToch implementation of "Real-time Scene Text Detection with Differentiable Binarization".

deepdetect icon deepdetect

Deep Learning API and Server in C++11 with Python bindings and support for Caffe, Tensorflow, XGBoost and TSNE

densenet-caffe icon densenet-caffe

DenseNet Caffe Models, converted from https://github.com/liuzhuang13/DenseNet

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.

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