YuQi9797

the-bottom-of-the-dialog-window

利用自定义Dialog实现仿ios底部弹框

YuQi9797.github.io

AFD_self

androidSources

博客中的源码ヾ(×× ) ﾂ

androidUtils

Utils

coolweather

CSBook

EagleEye

(ECCV'2020 Oral)EagleEye: Fast Sub-net Evaluation for Efficient Neural Network Pruning

GM-SCENet

ijkplayer

Android/iOS video player based on FFmpeg n3.4, with MediaCodec, VideoToolbox support.

imgclsmob

Sandbox for training convolutional networks for computer vision

java_mybatis

mybatis_reference

kfold

Kn实现的K折交叉验证

LRCN_PyTorch

NDKDemos

a series of NDK sample

Office-Automation

An office automation software customized for a Shanghai company focused on producing fire extinguishing equipments

OPEC-Net

Peeking into occluded joints: A novel framework for crowd pose estimation(ECCV2020)

Photograph

android 调用相机拍照。适配到Android 10

Pose-Track-Solutions

DeepBlue AI Team's Winner Solutions for CVWC 2019 Tiger Pose Track Challenge

pruning-from-scratch

PSA

This is an official implementation of "Polarized Self-Attention: Towards High-quality Pixel-wise Regression"

pytorch-cifar

95.47% on CIFAR10 with PyTorch

PyTorch-Deep-Learning-Template

A Pytorch Computer Vision template to quick start your next project! 🚀🚀

R2Plus1D-C3D

A PyTorch implementation of R2Plus1D and C3D based on CVPR 2017 paper "A Closer Look at Spatiotemporal Convolutions for Action Recognition" and CVPR 2014 paper "Learning Spatiotemporal Features with 3D Convolutional Networks"

robot

simple-faster-rcnn-pytorch

A simplified implemention of Faster R-CNN that replicate performance from origin paper

SMSSDK-for-Android

The convenience of the SDK message authentication code function integration

The-bottom-of-the-popup-window

利用PopupWindow实现仿ios底部弹框

UniPose

We propose UniPose, a unified framework for human pose estimation, based on our “Waterfall” Atrous Spatial Pooling architecture, that achieves state-of-art-results on several pose estimation metrics. Current pose estimation methods utilizing standard CNN architectures heavily rely on statistical postprocessing or predefined anchor poses for joint localization. UniPose incorporates contextual seg- mentation and joint localization to estimate the human pose in a single stage, with high accuracy, without relying on statistical postprocessing methods. The Waterfall module in UniPose leverages the efficiency of progressive filter- ing in the cascade architecture, while maintaining multi- scale fields-of-view comparable to spatial pyramid config- urations. Additionally, our method is extended to UniPose- LSTM for multi-frame processing and achieves state-of-the- art results for temporal pose estimation in Video. Our re- sults on multiple datasets demonstrate that UniPose, with a ResNet backbone and Waterfall module, is a robust and efficient architecture for pose estimation obtaining state-of- the-art results in single person pose detection for both sin- gle images and videos.