Hao Zhang (HaoMood)

HaoMood

Geek Repo

Company:YouTu Lab, Tencent

Location:Shenzhen, China

Home Page:https://haomood.github.io/homepage/

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Hao Zhang's repositories

bilinear-cnn

PyTorch implementation of bilinear CNN for fine-grained image recognition

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blinear-cnn-faster

A Faster PyTorch implementation of bilinear CNN for fine-grained image recognition

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File

Reference Files

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homepage

Hao Zhang's Homepage

ddt

Deep Descriptor Transforming for image retrieval

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crow

Python implementation of CroW for unsupervised image retrieval

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cpp-primer

Solution to C++ Primer, 5th edtion

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psychology

心理学笔记

fine-grained-baseline

Baseline results of fine-grained visual recognition

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pwa

Python implementation of PWA for image retrieval.

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vgg-16-bn

Train CIFAR-10 using VGG-16-BN, which gives 93.39% test set accuracy.

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vbird-linux

第13章 学习shell script

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3D-ResNets-PyTorch

3D ResNets for Action Recognition (CVPR 2018)

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6.189

MIT 6.189 Assignments and Projects

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6.s096-Effective-Programming-in-C-and-C-

Solution to assignments of MIT 6.s096 course

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dense_flow

Tools to extract dense optical flow from videos, based on OpenCV

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pytorch-utilities

Data loader and other utility files for PyTorch

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algorithm-data-structures

Common algorithms and data structures

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convert_torch_to_pytorch

Convert torch t7 model to pytorch model and source.

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data-mining

Assignments solutions to NJU Data Mining course

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digcircuit

A simulation of digital circuits.

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introduction-to-data-mining

Assignments of NJU Introdcution to Data Mining course

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pytorch-summary

Model summary in PyTorch similar to `model.summary()` in Keras

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R2Plus1D-PyTorch

PyTorch implementation of the R2Plus1D convolution based ResNet architecture described in the paper "A Closer Look at Spatiotemporal Convolutions for Action Recognition"

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temporal-segment-networks

Code & Models for Temporal Segment Networks (TSN) in ECCV 2016

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temporal-segment-networks-pytorch

A PyTorch implementation of temporal segment networks

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tsn-pytorch

Temporal Segment Networks (TSN) in PyTorch

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uncommon-datasets-caffe

use uncommon datasets on caffe,such as cifar100 and SVHN

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vision

Datasets, Transforms and Models specific to Computer Vision

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