wgan, wgan2(improved, gp), infogan, and dcgan implementation in lasagne, keras, pytorch

Overview

Generative Adversarial Notebooks

Collection of my Generative Adversarial Network implementations

Most codes are for python3, most notebooks works on

CycleGAN

  • CycleGAN-lasagne
  • CycleGAN-keras

CycleGAN results

Result after 3 hours and 58 epochs on a GTX 1080. From top to bottom: Input, Fake, Recreate of the input.

Face-off result. From top to bottom: Input, Fake, Recreate of the input. [youtube video](https://www.youtube.com/watch?v=Fea4kZq0oFQ)

pix2pix

  • pix2pix-keras: pix2pix GAN Keras implementation
  • pix2pix-lasagne: pix2pix GAN Lasagne implementation
  • pix2pix-torch: pix2pix GAN pytorch implementation

pix2pix sample results

Validation result of edges-to-shoes after 12 epochs. From top to bottom: Input, Ground truth, the result.

Validation result of facades dataset after 150 epochs using resnet. From top to bottom: Input, Ground truth, the result.

WGAN on CIFAR10

WGAN2 (improved WGAN/WGAN-gp)

  • wgan2-lasagne: improved WGAN Lasagne implementation (on CIFAR10)
  • wgan2-keras: improved WGAN Keras implementation (on CIFAR10)
  • wgan2-lasagne-anime: WGAN on anime face images, lasagne
  • wgan2-AC-lasagne: improved WGAN Lasagne implementation with Auxillary classfier

WGAN2 sample results

  • cifar10 dataset

  • cifar10 dataset with Auxillary classfier

  • anime face dataset

InfoGAN

  • mnist-infogan: InfoGAN Lasagne on MNIST dataset
  • mnist-infogan-paper-uniform: InfoGAN Lasagne on MNIST dataset (fllowing the paper implementation)

InfoGAN sample results

DCGAN

  • dcgan-lasagne: DCGAN in Lasagne

DCGAN sample results

Owner
tjwei
the avatar is generated by my Quick-Neural-Art-Transfer with a picture of Hatsune Miku
tjwei
[ICCV-2021] An Empirical Study of the Collapsing Problem in Semi-Supervised 2D Human Pose Estimation

An Empirical Study of the Collapsing Problem in Semi-Supervised 2D Human Pose Estimation (ICCV 2021) Introduction This is an official pytorch implemen

rongchangxie 42 Jan 04, 2023
Parameterized Explainer for Graph Neural Network

PGExplainer This is a Tensorflow implementation of the paper: Parameterized Explainer for Graph Neural Network https://arxiv.org/abs/2011.04573 NeurIP

Dongsheng Luo 89 Dec 12, 2022
A tool to estimate time varying instantaneous reproduction number during epidemics

EpiEstim A tool to estimate time varying instantaneous reproduction number during epidemics. It is described in the following paper: @article{Cori2013

MRC Centre for Global Infectious Disease Analysis 78 Dec 19, 2022
PyTorch Code for the paper "VSE++: Improving Visual-Semantic Embeddings with Hard Negatives"

Improving Visual-Semantic Embeddings with Hard Negatives Code for the image-caption retrieval methods from VSE++: Improving Visual-Semantic Embeddings

Fartash Faghri 441 Dec 05, 2022
Reinforcement Learning Theory Book (rus)

Reinforcement Learning Theory Book (rus)

qbrick 206 Nov 27, 2022
[CVPR 2020] Transform and Tell: Entity-Aware News Image Captioning

Transform and Tell: Entity-Aware News Image Captioning This repository contains the code to reproduce the results in our CVPR 2020 paper Transform and

Alasdair Tran 85 Dec 13, 2022
Theory-inspired Parameter Control Benchmarks for Dynamic Algorithm Configuration

This repo is for the paper: Theory-inspired Parameter Control Benchmarks for Dynamic Algorithm Configuration The DAC environment is based on the Dynam

Carola Doerr 1 Aug 19, 2022
Code for CVPR 2021 paper TransNAS-Bench-101: Improving Transferrability and Generalizability of Cross-Task Neural Architecture Search.

TransNAS-Bench-101 This repository contains the publishable code for CVPR 2021 paper TransNAS-Bench-101: Improving Transferrability and Generalizabili

Yawen Duan 17 Nov 20, 2022
VQGAN+CLIP Colab Notebook with user-friendly interface.

VQGAN+CLIP and other image generation system VQGAN+CLIP Colab Notebook with user-friendly interface. Latest Notebook: Mse regulized zquantize Notebook

Justin John 227 Jan 05, 2023
TiP-Adapter: Training-free CLIP-Adapter for Better Vision-Language Modeling

TiP-Adapter: Training-free CLIP-Adapter for Better Vision-Language Modeling This is the official code release for the paper 'TiP-Adapter: Training-fre

peng gao 189 Jan 04, 2023
Calculates JMA (Japan Meteorological Agency) seismic intensity (shindo) scale from acceleration data recorded in NumPy array

shindo.py Calculates JMA (Japan Meteorological Agency) seismic intensity (shindo) scale from acceleration data stored in NumPy array Introduction Japa

RR_Inyo 3 Sep 23, 2022
Using python and scikit-learn to make stock predictions

MachineLearningStocks in python: a starter project and guide EDIT as of Feb 2021: MachineLearningStocks is no longer actively maintained MachineLearni

Robert Martin 1.3k Dec 29, 2022
ARAE-Tensorflow for Discrete Sequences (Adversarially Regularized Autoencoder)

ARAE Tensorflow Code Code for the paper Adversarially Regularized Autoencoders for Generating Discrete Structures by Zhao, Kim, Zhang, Rush and LeCun

19 Nov 12, 2021
Learning embeddings for classification, retrieval and ranking.

StarSpace StarSpace is a general-purpose neural model for efficient learning of entity embeddings for solving a wide variety of problems: Learning wor

Facebook Research 3.8k Dec 22, 2022
A PaddlePaddle version of Neural Renderer, refer to its PyTorch version

Neural 3D Mesh Renderer in PadddlePaddle A PaddlePaddle version of Neural Renderer, refer to its PyTorch version Install Run: pip install neural-rende

AgentMaker 13 Jul 12, 2022
This is the offical website for paper ''Category-consistent deep network learning for accurate vehicle logo recognition''

The Pytorch Implementation of Category-consistent deep network learning for accurate vehicle logo recognition This is the offical website for paper ''

Wanglong Lu 28 Oct 29, 2022
Multitask Learning Strengthens Adversarial Robustness

Multitask Learning Strengthens Adversarial Robustness

Columbia University 15 Jun 10, 2022
Boost learning for GNNs from the graph structure under challenging heterophily settings. (NeurIPS'20)

Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs Jiong Zhu, Yujun Yan, Lingxiao Zhao, Mark Heimann, Leman Akoglu,

GEMS Lab: Graph Exploration & Mining at Scale, University of Michigan 70 Dec 18, 2022
Supporting code for "Autoregressive neural-network wavefunctions for ab initio quantum chemistry".

naqs-for-quantum-chemistry This repository contains the codebase developed for the paper Autoregressive neural-network wavefunctions for ab initio qua

Tom Barrett 24 Dec 23, 2022
tensorflow code for inverse face rendering

InverseFaceRender This is tensorflow code for our project: Learning Inverse Rendering of Faces from Real-world Videos. (https://arxiv.org/abs/2003.120

Yuda Qiu 18 Nov 16, 2022