A torch implementation of "Pixel-Level Domain Transfer"

Overview

Pixel Level Domain Transfer

A torch implementation of "Pixel-Level Domain Transfer". based on dcgan.torch.

Dataset

The dataset used is "LookBook", from Donggeun Yoo.

Training

To train the model, put the LOOKBOOK dataset under repository, resize images to 64*64. Prepare the dataset using prepare_data.ipynb. Then run

th main.lua

You can tune the parameters, such as number of filters, optimizer, etc.

Example results

Example results on LOOKBOOK dataset(top), left is input, right is generated clothes. Results on a similar dataset (bottom). More results will be added soon.

Results

Monitor the performance

  • Install display package with: luarocks install https://raw.githubusercontent.com/szym/display/master/display-scm-0.rockspec
  • Start the server with: th -ldisplay.start
  • Open this URL in your browser: http://localhost:8000

Below shows the results after 7 epochs, each 3*1 block is generated cloth, true cloth, input image. Errors of G, D, and A network will be plotted.

epoch 7

Owner
Fei Xia
Research Scientist @google-research, previously Ph.D. @StanfordVL @cvgl Computer Vision and Robotics
Fei Xia
Convert weight file.pth to weight file.blob

CONVERT YOUR MODEL TO IR FORMAT INSTALLATION OpenVino Toolkit Download openvinotoolkit 2021.3 version : Link Instruction of installation : Link Pytorc

Tran Anh Tuan 3 Nov 18, 2021
Public implementation of the Convolutional Motif Kernel Network (CMKN) architecture

CMKN Implementation of the convolutional motif kernel network (CMKN) introduced in Ditz et al., "Convolutional Motif Kernel Network", 2021. Testing Yo

1 Nov 17, 2021
Code for "Learning Graph Cellular Automata"

Learning Graph Cellular Automata This code implements the experiments from the NeurIPS 2021 paper: "Learning Graph Cellular Automata" Daniele Grattaro

Daniele Grattarola 37 Oct 26, 2022
Show Me the Whole World: Towards Entire Item Space Exploration for Interactive Personalized Recommendations

HierarchicyBandit Introduction This is the implementation of WSDM 2022 paper : Show Me the Whole World: Towards Entire Item Space Exploration for Inte

yu song 5 Sep 09, 2022
A Comprehensive Empirical Study of Vision-Language Pre-trained Model for Supervised Cross-Modal Retrieval

CLIP4CMR A Comprehensive Empirical Study of Vision-Language Pre-trained Model for Supervised Cross-Modal Retrieval The original data and pre-calculate

24 Dec 26, 2022
FinGAT: A Financial Graph Attention Networkto Recommend Top-K Profitable Stocks

FinGAT: A Financial Graph Attention Networkto Recommend Top-K Profitable Stocks This is our implementation for the paper: FinGAT: A Financial Graph At

Yu-Che Tsai 64 Dec 13, 2022
Image morphing without reference points by applying warp maps and optimizing over them.

Differentiable Morphing Image morphing without reference points by applying warp maps and optimizing over them. Differentiable Morphing is machine lea

Alex K 380 Dec 19, 2022
Este conversor criará a medida exata para sua receita de capuccino gelado da grandiosa Rafaella Ballerini!

ConversorDeMedidas_CapuccinoGelado Este conversor criará a medida exata para sua receita de capuccino gelado da grandiosa Rafaella Ballerini! Requirem

Arthur Ottoni Ribeiro 48 Nov 15, 2022
Semantic Edge Detection with Diverse Deep Supervision

Semantic Edge Detection with Diverse Deep Supervision This repository contains the code for our IJCV paper: "Semantic Edge Detection with Diverse Deep

Yun Liu 12 Dec 31, 2022
Jupyter notebooks for the code samples of the book "Deep Learning with Python"

Jupyter notebooks for the code samples of the book "Deep Learning with Python"

François Chollet 16.2k Dec 30, 2022
RRL: Resnet as representation for Reinforcement Learning

Resnet as representation for Reinforcement Learning (RRL) is a simple yet effective approach for training behaviors directly from visual inputs. We demonstrate that features learned by standard image

Meta Research 21 Dec 07, 2022
Bottleneck Transformers for Visual Recognition

Bottleneck Transformers for Visual Recognition Experiments Model Params (M) Acc (%) ResNet50 baseline (ref) 23.5M 93.62 BoTNet-50 18.8M 95.11% BoTNet-

Myeongjun Kim 236 Jan 03, 2023
Official implementation of VQ-Diffusion

Official implementation of VQ-Diffusion: Vector Quantized Diffusion Model for Text-to-Image Synthesis

Microsoft 592 Jan 03, 2023
Pathdreamer: A World Model for Indoor Navigation

Pathdreamer: A World Model for Indoor Navigation This repository hosts the open source code for Pathdreamer, to be presented at ICCV 2021. Paper | Pro

Google Research 122 Jan 04, 2023
Lightweight Salient Object Detection in Optical Remote Sensing Images via Feature Correlation

CorrNet This project provides the code and results for 'Lightweight Salient Object Detection in Optical Remote Sensing Images via Feature Correlation'

Gongyang Li 13 Nov 03, 2022
Multi Agent Path Finding Algorithms

MATP-solver Simulator collision check path step random initial states or given states Traditional method Seperate A* algorithem Confict-based Search S

30 Dec 12, 2022
Evolutionary Population Curriculum for Scaling Multi-Agent Reinforcement Learning

Evolutionary Population Curriculum for Scaling Multi-Agent Reinforcement Learning This is the code for implementing the MADDPG algorithm presented in

97 Dec 21, 2022
Fully Connected DenseNet for Image Segmentation

Fully Connected DenseNets for Semantic Segmentation Fully Connected DenseNet for Image Segmentation implementation of the paper The One Hundred Layers

Somshubra Majumdar 84 Oct 31, 2022
Official implementation of the paper "Steganographer Detection via a Similarity Accumulation Graph Convolutional Network"

SAGCN - Official PyTorch Implementation | Paper | Project Page This is the official implementation of the paper "Steganographer detection via a simila

ZHANG Zhi 1 Nov 26, 2021
WTTE-RNN a framework for churn and time to event prediction

WTTE-RNN Weibull Time To Event Recurrent Neural Network A less hacky machine-learning framework for churn- and time to event prediction. Forecasting p

Egil Martinsson 727 Dec 28, 2022