Implementation of CVPR 2021 paper "Spatially-invariant Style-codes Controlled Makeup Transfer"

Related tags

Deep LearningSCGAN
Overview

SCGAN

Implementation of CVPR 2021 paper "Spatially-invariant Style-codes Controlled Makeup Transfer"

Prepare

The pre-trained model is avaiable at https://drive.google.com/file/d/1t1Hbgqqzc_rV5v3gF7HuJ-xiuEVNb8sh/view?usp=sharing.

vgg_conv.pth:https://drive.google.com/file/d/1JNrSVZrK4TfC7pFG-r7AOmGvBXF2VFOt/view?usp=sharing

Put the G.pth and VGG weights in "./checkpoints" and "./" respectively.

Environments:python=3.8, pytorch=1.6.0, Ubuntu=20.04.1 LTS

Train

Put the train-list of makeup images in "./MT-Dataset/makeup.txt" and the train-list of non-makeup images in "./MT-Dataset/non-makeup.txt"

Use the "./scripts/handle_parsing.py" to convert the origin MT-Dataset's seg labels

Use python sc.py --phase train to train

Test

1.Global Makeup Transfer

python sc.py --phase test

Global Makeup Transfer

2.Part-specific Makeup Transfer

python sc.py --phase test --partial

Part-specific Makeup Transfer

3.Global Interpolation

python sc.py --phase test --interpolation

Global Interpolation

4.Part-specific Interpolation

python sc.py --phase test --partial --interpolation

Part-specific Interpolation

PyExplainer: A Local Rule-Based Model-Agnostic Technique (Explainable AI)

PyExplainer PyExplainer is a local rule-based model-agnostic technique for generating explanations (i.e., why a commit is predicted as defective) of J

AI Wizards for Software Management (AWSM) Research Group 14 Nov 13, 2022
SHRIMP: Sparser Random Feature Models via Iterative Magnitude Pruning

SHRIMP: Sparser Random Feature Models via Iterative Magnitude Pruning This repository is the official implementation of "SHRIMP: Sparser Random Featur

Bobby Shi 0 Dec 16, 2021
A benchmark framework for Tensorflow

TensorFlow benchmarks This repository contains various TensorFlow benchmarks. Currently, it consists of two projects: PerfZero: A benchmark framework

1.1k Dec 30, 2022
Simple PyTorch hierarchical models.

A python package adding basic hierarchal networks in pytorch for classification tasks. It implements a simple hierarchal network structure based on feed-backward outputs.

Rajiv Sarvepalli 5 Mar 06, 2022
pytorch implementation of openpose including Hand and Body Pose Estimation.

pytorch-openpose pytorch implementation of openpose including Body and Hand Pose Estimation, and the pytorch model is directly converted from openpose

Hzzone 1.4k Jan 07, 2023
Pgn2tex - Scripts to convert pgn files to latex document. Useful to build books or pdf from pgn studies

Pgn2Latex (WIP) A simple script to make pdf from pgn files and studies. It's sti

12 Jul 23, 2022
🦙 LaMa Image Inpainting, Resolution-robust Large Mask Inpainting with Fourier Convolutions, WACV 2022

🦙 LaMa Image Inpainting, Resolution-robust Large Mask Inpainting with Fourier Convolutions, WACV 2022

Advanced Image Manipulation Lab @ Samsung AI Center Moscow 4.7k Dec 31, 2022
Code for the paper One Thing One Click: A Self-Training Approach for Weakly Supervised 3D Semantic Segmentation, CVPR 2021.

One Thing One Click One Thing One Click: A Self-Training Approach for Weakly Supervised 3D Semantic Segmentation (CVPR2021) Code for the paper One Thi

44 Dec 12, 2022
Bulk2Space is a spatial deconvolution method based on deep learning frameworks

Bulk2Space Spatially resolved single-cell deconvolution of bulk transcriptomes using Bulk2Space Bulk2Space is a spatial deconvolution method based on

Dr. FAN, Xiaohui 60 Dec 27, 2022
Generating Fractals on Starknet with Cairo

StarknetFractals Generating the mandelbrot set on Starknet Current Implementation generates 1 pixel of the fractal per call(). It takes a few minutes

Orland0x 10 Jul 16, 2022
A Python library for adversarial machine learning focusing on benchmarking adversarial robustness.

ARES This repository contains the code for ARES (Adversarial Robustness Evaluation for Safety), a Python library for adversarial machine learning rese

Tsinghua Machine Learning Group 377 Dec 20, 2022
[ICCV 2021 Oral] NerfingMVS: Guided Optimization of Neural Radiance Fields for Indoor Multi-view Stereo

NerfingMVS Project Page | Paper | Video | Data NerfingMVS: Guided Optimization of Neural Radiance Fields for Indoor Multi-view Stereo Yi Wei, Shaohui

Yi Wei 369 Dec 24, 2022
Machine learning framework for both deep learning and traditional algorithms

NeoML is an end-to-end machine learning framework that allows you to build, train, and deploy ML models. This framework is used by ABBYY engineers for

NeoML 704 Dec 27, 2022
(CVPR 2022) Pytorch implementation of "Self-supervised transformers for unsupervised object discovery using normalized cut"

(CVPR 2022) TokenCut Pytorch implementation of Tokencut: Self-supervised Transformers for Unsupervised Object Discovery using Normalized Cut Yangtao W

YANGTAO WANG 200 Jan 02, 2023
Single Image Random Dot Stereogram for Tensorflow

TensorFlow-SIRDS Single Image Random Dot Stereogram for Tensorflow SIRDS is a means to present 3D data in a 2D image. It allows for scientific data di

Greg Peatfield 5 Aug 10, 2022
A hybrid framework (neural mass model + ML) for SC-to-FC prediction

The current workflow simulates brain functional connectivity (FC) from structural connectivity (SC) with a neural mass model. Gradient descent is applied to optimize the parameters in the neural mass

Yilin Liu 1 Jan 26, 2022
NOD: Taking a Closer Look at Detection under Extreme Low-Light Conditions with Night Object Detection Dataset

NOD (Night Object Detection) Dataset NOD: Taking a Closer Look at Detection under Extreme Low-Light Conditions with Night Object Detection Dataset, BM

Igor Morawski 17 Nov 05, 2022
How to train a CNN to 99% accuracy on MNIST in less than a second on a laptop

Training a NN to 99% accuracy on MNIST in 0.76 seconds A quick study on how fast you can reach 99% accuracy on MNIST with a single laptop. Our answer

Tuomas Oikarinen 42 Dec 10, 2022
Expert Finding in Legal Community Question Answering

Expert Finding in Legal Community Question Answering Arian Askari, Suzan Verberne, and Gabriella Pasi. Expert Finding in Legal Community Question Answ

Arian Askari 3 Oct 31, 2022
[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