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odps

MaxCompute

opencv3-intro-book-src

:blue_book:《OpenCV3编程入门》书本配套源码 |《Introduction to OpenCV3 Programming》Book Source Code

pacnn-perspectiveaware-crowdcounting

Perspective-Aware CNN for Crowd Counting

pcc-net

PCC Net: Perspective Crowd Counting via Spatial Convolutional Network

pcl

PyTorch code for "Prototypical Contrastive Learning of Unsupervised Representations"

pix2pix.pytorch

A pytorch implementation of "Image-to-Image Translation with Conditional Adversarial Networks"

powerful-gnns

How Powerful are Graph Neural Networks?

pseudo-3d-residual-networks

Pseudo-3D Convolutional Residual Networks for Video Representation Learning

pytorch-cyclegan-and-pix2pix

Image-to-image translation in PyTorch (e.g., horse2zebra, edges2cats, and more)

pytorch-spectral-normalization-gan

Paper by Miyato et al. https://openreview.net/forum?id=B1QRgziT-

pytorch-ssim

pytorch structural similarity (SSIM) loss

qrec

QRec: A Python Framework for quick implementation of recommender systems (TensorFlow Based)

r-c3d.pytorch

R-C3D pytorch implementation

r2plus1d

R(2+1)D and Mixed-Convolutions for Action Recognition.

self-attention-gan

Pytorch implementation of Self-Attention Generative Adversarial Networks (SAGAN)

senet.pytorch

PyTorch implementation of SENet

sparseprop

Temporal action proposals

spectral-clustering-with-graph-neural-networks-for-graph-pooling

Experimental results obtained with the MinCutPool layer as presented in the 2020 ICML paper "Spectral Clustering with Graph Neural Networks for Graph Pooling"

stock-prediction-models

Gathers machine learning and deep learning models for Stock forecasting, included trading bots and simulations

stockpredictionai

In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.

swav

PyTorch implementation of SwAV https//arxiv.org/abs/2006.09882

swgmm

Sliced Wasserstein Distance for Learning Gaussian Mixture Models

tensorboard

A simple example for visualizing tf-code

tfsegmentation

RTSeg: Real-time Semantic Segmentation Comparative Study

transferlearning

Everything about Transfer Learning and Domain Adaptation--迁移学习

vae-gmvae

This repository contains the implementation of the VAE and Gaussian Mixture VAE using TensorFlow and several network architectures

vehicle_counting_tensorflow

"MORE THAN VEHICLE COUNTING!" This project provides prediction for speed, color and size of the vehicles with TensorFlow Object Counting API.

video-classification-3d-cnn-pytorch

Video classification tools using 3D ResNet

video_analysis

video_lstm