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wyzhe's Projects

grids icon grids

Implementation of the MILP-based grid-layout generation algorithm

icdar2019_ctdar icon icdar2019_ctdar

The ICDAR 2019 cTDaR is to evaluate the performance of methods for table detection (TRACK A) and table recognition (TRACK B). For the first track, document images containing one or several tables are provided. For TRACK B two subtracks exist: the first subtrack (B.1) provides the table region. Thus, only the table structure recognition must be performed. The second subtrack (B.2) provides no a-priori information. This means, the table region and table structure detection has to be done.

leetcodeanimation icon leetcodeanimation

Demonstrate all the questions on LeetCode in the form of animation.(用动画的形式呈现解LeetCode题目的思路)

liif icon liif

Learning Continuous Image Representation with Local Implicit Image Function

megengine icon megengine

MegEngine 是一个快速、可拓展、易于使用且支持自动求导的数值计算框架

mvision icon mvision

机器人视觉 移动机器人 VS-SLAM ORB-SLAM2 深度学习目标检测 yolov3 行为检测 opencv PCL 机器学习 无人驾驶

nni icon nni

An open source AutoML toolkit for neural architecture search, model compression and hyper-parameter tuning.

nsfw_data_scraper icon nsfw_data_scraper

Collection of scripts to aggregate image data for the purposes of training an NSFW Image Classifier

pfnn icon pfnn

Phase-Functioned Neural Networks for Character Control

pyretri icon pyretri

Open source deep learning based unsupervised image retrieval toolbox built on PyTorch🔥

pytorch icon pytorch

Tensors and Dynamic neural networks in Python with strong GPU acceleration

rnan icon rnan

PyTorch code for our ICLR 2019 paper "Residual Non-local Attention Networks for Image Restoration"

san icon san

Second-order Attention Network for Single Image Super-resolution (CVPR-2019)

sparser-cnn icon sparser-cnn

End-to-End Object Detection with Learnable Proposal

spsr icon spsr

Pytorch implementation of Structure-Preserving Super Resolution with Gradient Guidance (CVPR 2020)

surat icon surat

implementation based on "Audio-Driven Facial Animation by Joint End-to-End Learning of Pose and Emotion"

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