• 1
• 0
• 0

pyq / vue-admin-template

a vue2.0 minimal admin template

• 1
• 1
• 0

pyq / SmallObjectAugmentation

Simple implementation of augmentation for small object detection

• 1
• 0
• 2

pyq / awesome-tiny-object-detection

🕶 A curated list of Tiny Object Detection papers and related resources.

• 1
• 2
• 1

pyq / DSSD

Pytorch implementation of DSSD (Deconvolutional Single Shot Detector)

• 1
• 0
• 0

pyq / mAP

mean Average Precision - This code evaluates the performance of your neural net for object recognition.

• 1
• 0
• 0

pyq / Detectron

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

• 1
• 0
• 0

pyq / CVPR-Paper

cvpr2020/cvpr2019／cvpr2018/cvpr2017 papers，极市团队整理

• 1
• 0
• 0

pyq / ResNeSt

ResNeSt: Split-Attention Networks

• 1
• 0
• 0

pyq / ResNeXt-PyTorch

• 1
• 0
• 0

pyq / cocoapi

Clone of COCO API - Dataset @ http://cocodataset.org/ - with changes to support Windows build and python3

• 1
• 0
• 0

pyq / res2net-plus

Res2Net architecture with improved stem and Mish activation function

• 1
• 0
• 0

pyq / cutMix-Pytorch

Official Pytorch implementation of CutMix regularizer

• 1
• 0
• 0

pyq / ResidualAttentionNetwork-pytorch

a pytorch code about Residual Attention Network. This code is based on two projects from

• 1
• 0
• 0

pyq / Res2Net-PretrainedModels

(ImageNet pretrained models) The official pytorch implemention of the TPAMI paper "Res2Net: A New Multi-scale Backbone Architecture"

• 1
• 0
• 0

pyq / SKNet

Code for our CVPR 2019 paper: Selective Kernel Networks; See zhihu：https://zhuanlan.zhihu.com/p/59690223

• 1
• 0
• 0

pyq / senet

PyTorch implementation of SENet

• 1
• 0
• 0

pyq / resnet

Datasets, Transforms and Models specific to Computer Vision

• 1
• 0
• 1

pyq / ssd-pytorch

这是一个ssd-pytorch的源码，可以用于训练自己的模型。

• 1
• 0
• 0

pyq / pumpkin-book

《机器学习》（西瓜书）公式推导解析，在线阅读地址：https://datawhalechina.github.io/pumpkin-book

• 1
• 0
• 0

pyq / dropblock

Implementation of DropBlock: A regularization method for convolutional networks in PyTorch.