Pinned Repositories
AdderNet
Code for paper " AdderNet: Do We Really Need Multiplications in Deep Learning?"
closed-form-matting
Python implementation of A. Levin D. Lischinski and Y. Weiss. A Closed Form Solution to Natural Image Matting. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), June 2006, New York
cocoapi
Clone of COCO API - Dataset @ http://cocodataset.org/ - with changes to support Windows build and python3
DeepLearning-500-questions
深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为18个章节，50余万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作，联系scutjy2015@163.com 版权所有，违权必究 Tan 2018.06
dl-vision-papers
深度学习和三维视觉相关的论文
facenet
Face recognition using Tensorflow
GraphCut
Graph cut image segmentation with custom GUI.
HRNet-MaskRCNN-Benchmark
Object detection with multi-level representations generated from deep high-resolution representation learning (HRNetV2h).
ImageProcessing100Wen
「画像処理100本ノック」中文版本！为图像处理初学者设计的 100 个问题。
LearnPython
以撸代码的形式学习Python
DavideHe's Repositories
DavideHe/ImageProcessing100Wen
「画像処理100本ノック」中文版本！为图像处理初学者设计的 100 个问题。
DavideHe/AdderNet
Code for paper " AdderNet: Do We Really Need Multiplications in Deep Learning?"
DavideHe/closed-form-matting
Python implementation of A. Levin D. Lischinski and Y. Weiss. A Closed Form Solution to Natural Image Matting. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), June 2006, New York
DavideHe/cocoapi
Clone of COCO API - Dataset @ http://cocodataset.org/ - with changes to support Windows build and python3
DavideHe/DeepLearning-500-questions
深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为18个章节，50余万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作，联系scutjy2015@163.com 版权所有，违权必究 Tan 2018.06
DavideHe/DeshadowNet
[CVPR2017] DeshadowNet implementation
DavideHe/dl-vision-papers
深度学习和三维视觉相关的论文
DavideHe/facenet
Face recognition using Tensorflow
DavideHe/fastai
The fastai deep learning library
DavideHe/GraphCut
Graph cut image segmentation with custom GUI.
DavideHe/HRNet-MaskRCNN-Benchmark
Object detection with multi-level representations generated from deep high-resolution representation learning (HRNetV2h).
DavideHe/LearnPython
以撸代码的形式学习Python
DavideHe/mae
PyTorch implementation of MAE https//arxiv.org/abs/2111.06377
DavideHe/maskrcnn-benchmark
Fast, modular reference implementation of Instance Segmentation and Object Detection algorithms in PyTorch.
DavideHe/mobilenetv2.pytorch
72.8% MobileNetV2 1.0 model on ImageNet and a spectrum of pre-trained MobileNetV2 models
DavideHe/mobilevit-pytorch
A PyTorch implementation of "MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision Transformer".
DavideHe/models
Models and examples built with TensorFlow
DavideHe/neuralgym
Deep Learning Toolkit
DavideHe/openTSNE
Extensible, parallel implementations of t-SNE
DavideHe/semantic-segmentation-pytorch
Pytorch implementation for Semantic Segmentation/Scene Parsing on MIT ADE20K dataset
DavideHe/swa_demo
stochastic weight averaging demo
DavideHe/tensorpack
A Neural Net Training Interface on TensorFlow, with focus on speed + flexibility
DavideHe/tf-hrnet
tensorflow implementation for "High-Resolution Representations for Labeling Pixels and Regions"
DavideHe/tf-slim
DavideHe/tsne-viz
Python Wrapper for t-SNE Visualization
DavideHe/Visualize-feature-maps-and-heatmap
可视化特征热力图
DavideHe/VTL
vision_tools_lib
DavideHe/yacs
YACS -- Yet Another Configuration System
DavideHe/yolact
A simple, fully convolutional model for real-time instance segmentation.