Feesics

Pinned Repositories

Algorithm_for_Interview-Chinese
Algorithm for Interview（面试算法笔记-中文）
Language:C++0 1 00
AlignedReID
Alignedreid＋+: Dynamically Matching Local Information for Person Re-Identification.
Language:Python00
batch-feature-erasing-network
Official source code of Batch Feature Erasing for Person Re-identification and Beyond
Language:Python00
Bottom-up-Clustering-Person-Re-identification
A Bottom-Up Clustering Approach to Unsupervised Person Re-identification, AAAI 2019 (Oral)
Language:Python00
C-code
C++基础知识
00
caffe-tensorflow
Caffe models in TensorFlow
Language:Python0 1 00
CCPD
[ECCV 2018] CCPD: a diverse and well-annotated dataset for license plate detection and recognition
Language:Python0 1 00
cluster
代码实现所有数据集的K-means，FCM，谱聚类，DBSCAN，AP（AffinityPropagation），DPC聚类算法比较
Language:MATLAB00
CodingInterviewChinese2
《剑指Offer》第二版源代码
Language:C++00
CosFace
Tensorflow implementation for paper CosFace: Large Margin Cosine Loss for Deep Face Recognition
Language:Python00

Feesics's Repositories

Feesics/AlignedReID
Alignedreid＋+: Dynamically Matching Local Information for Person Re-Identification.
Language:Python00
Feesics/DCGAN-tensorflow
A tensorflow implementation of "Deep Convolutional Generative Adversarial Networks"
Language:JavaScript
Feesics/Deep-Learning-Interview-Book
深度学习面试宝典（含数学、机器学习、深度学习、计算机视觉、自然语言处理和SLAM等方向）
Feesics/deep-person-reid
Pytorch framework for deep-learning person re-identification.
Language:Python
Feesics/DMCRID-MulCAM-reID
An implementation of the person re-identification
Language:Python
Feesics/Generative-Adversarial-Networks-Roadmap
The Roadmap to Learn Generative Adversarial Networks (GANs)
Language:Python
Feesics/HDIL-DIP
数字图像处理 | C & Matlab
Feesics/HeatMap-in-person-re-identification
如何在行人重识别领域针对图像画出热度图
Language:Python
Feesics/interview
📚 C/C++面试基础知识总结
Language:C++1 0
Feesics/keras_siamese_networks
A siamese network model of keras, include a data generator for big-data-training. Used contrastive loss .
Language:Python
Feesics/leetcode-cn
Feesics/linux-command
Linux命令大全搜索工具，内容包含Linux命令手册、详解、学习、搜集。https://git.io/linux
Language:HTML
Feesics/lvdmaaten.github.io
Website of Laurens van der Maaten
Language:JavaScript
Feesics/Multicore-TSNE
Parallel t-SNE implementation with Python and Torch wrappers.
Language:C++
Feesics/open-reid
Open source person re-identification library in python
Language:Python
Feesics/person-re-ranking
Person Re-ranking (CVPR 2017)
Language:Jupyter Notebook
Feesics/Person-reID-triplet-loss
Person re-ID baseline with triplet loss
Language:Python
Feesics/Person_reID_baseline_pytorch
A tiny, friendly, strong pytorch implement of person re-identification baseline. Tutorial 👉https://github.com/layumi/Person_reID_baseline_pytorch/tree/master/tutorial
Language:Python
Feesics/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
Feesics/Python-100-Days
Python - 100天从新手到大师
Language:Jupyter Notebook
Feesics/pytorch-cnn-visualizations
Pytorch implementation of convolutional neural network visualization techniques
Language:Python
Feesics/PyTorch-GAN
PyTorch implementations of Generative Adversarial Networks.
Language:Python
Feesics/SFT-ReID
My implementation of Spectral-Feature-Transformation-ReID, link to the paper: https://arxiv.org/abs/1811.11405
Language:Python
Feesics/SiamVGG
SiamVGG: Visual Tracking with Deeper Siamese Networks
Language:Python
Feesics/SiGAN
SiGAN: Siamese Generative Adversarial Network for Identity-Preserving Face Hallucination
Language:Python1 0
Feesics/SN_loss_for_reID
code for "Support Neighbor Loss for Person Re-Identification, ACM MM 2018"
Language:Python
Feesics/Spatial-Temporal-Re-identification
Spatial-Temporal Re-identification
Language:Python
Feesics/SphereReID
My implementation of paper: SphereReID: Deep Hypersphere Manifold Embedding for Person Re-Identification
Language:Python
Feesics/triplet-reid
Code for reproducing the results of our "In Defense of the Triplet Loss for Person Re-Identification" paper.
Language:Python1 0
Feesics/visdom
A flexible tool for creating, organizing, and sharing visualizations of live, rich data. Supports Torch and Numpy.
Language:Python1 0