Implementation of StyleSpace Analysis: Disentangled Controls for StyleGAN Image Generation in PyTorch

Last update: Dec 07, 2022

Related tags

Overview

StyleSpace Analysis: Disentangled Controls for StyleGAN Image Generation

Implementation of StyleSpace Analysis: Disentangled Controls for StyleGAN Image Generation (https://arxiv.org/pdf/2011.12799.pdf) in PyTorch

This implementation is mostly relied on rosinality's stylegan2-pytorch

Requirements

I have tested on:

PyTorch 1.3.1
CUDA 10.1

Usage

For the index and channel, please check the paper (https://arxiv.org/pdf/2011.12799.pdf), e.g., (11_286), channel 286 of generator level 11.

FFHQ

Firstly, you should download pretrained model from here and place the stylegan2-ffhq-config-f.pkl into pretrained folder.
Open the notebook StyleSpace_FFHQ.ipynb

Car

Comming soon

LSUN

Comming soon

Credit

The pretrained model weights are from https://github.com/NVlabs/stylegan2 and converted with https://github.com/rosinality/stylegan2-pytorch

Owner

Xuanchi Ren

Fight for future

GitHub Repository

Code release for Local Light Field Fusion at SIGGRAPH 2019

Local Light Field Fusion Project | Video | Paper Tensorflow implementation for novel view synthesis from sparse input images. Local Light Field Fusion

1.1k Dec 27, 2022

[NeurIPS 2019] Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss

Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss Kaidi Cao, Colin Wei, Adrien Gaidon, Nikos Arechiga, Tengyu Ma This is the offi

528 Jan 01, 2023

Facial detection, landmark tracking and expression transfer library for Windows, Linux and Mac

Welcome to the CSIRO Face Analysis SDK. Documentation for the SDK can be found in doc/documentation.html. All code in this SDK is provided according t

7 Jul 16, 2020

Implementation of Hierarchical Transformer Memory (HTM) for Pytorch

Hierarchical Transformer Memory (HTM) - Pytorch Implementation of Hierarchical Transformer Memory (HTM) for Pytorch. This Deepmind paper proposes a si

63 Dec 29, 2022

Swin-Transformer is basically a hierarchical Transformer whose representation is computed with shifted windows.

Swin-Transformer Swin-Transformer is basically a hierarchical Transformer whose representation is computed with shifted windows. For more details, ple

9 Mar 14, 2022

Code for the ICCV'21 paper "Context-aware Scene Graph Generation with Seq2Seq Transformers"

ICCV'21 Context-aware Scene Graph Generation with Seq2Seq Transformers Authors: Yichao Lu*, Himanshu Rai*, Cheng Chang*, Boris Knyazev†, Guangwei Yu,

37 Dec 18, 2022

Multi-Target Adversarial Frameworks for Domain Adaptation in Semantic Segmentation

Multi-Target Adversarial Frameworks for Domain Adaptation in Semantic Segmentation Paper Multi-Target Adversarial Frameworks for Domain Adaptation in

20 Jun 21, 2022

Official Implementation for the "An Empirical Investigation of 3D Anomaly Detection and Segmentation" paper.

An Empirical Investigation of 3D Anomaly Detection and Segmentation Project | Paper Official PyTorch Implementation for the "An Empirical Investigatio

55 Dec 14, 2022

A series of convenience functions to make basic image processing operations such as translation, rotation, resizing, skeletonization, and displaying Matplotlib images easier with OpenCV and Python.

imutils A series of convenience functions to make basic image processing functions such as translation, rotation, resizing, skeletonization, and displ

4.3k Jan 08, 2023

Official implementation of Densely connected normalizing flows

Densely connected normalizing flows This repository is the official implementation of NeurIPS 2021 paper Densely connected normalizing flows. Poster a

31 Dec 12, 2022

This is the unofficial code of Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes. which achieve state-of-the-art trade-off between accuracy and speed on cityscapes and camvid, without using inference acceleration and extra data

Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes Introduction This is the unofficial code of Deep Dual-re

113 Dec 23, 2022

Commonality in Natural Images Rescues GANs: Pretraining GANs with Generic and Privacy-free Synthetic Data - Official PyTorch Implementation (CVPR 2022)

Commonality in Natural Images Rescues GANs: Pretraining GANs with Generic and Privacy-free Synthetic Data (CVPR 2022) Potentials of primitive shapes f

31 Sep 27, 2022

"Moshpit SGD: Communication-Efficient Decentralized Training on Heterogeneous Unreliable Devices", official implementation

Moshpit SGD: Communication-Efficient Decentralized Training on Heterogeneous Unreliable Devices This repository contains the official PyTorch implemen

21 Oct 18, 2022