Official PyTorch code for the paper: "Point-Based Modeling of Human Clothing" (ICCV 2021)

Overview

Point-Based Modeling of Human Clothing

Paper | Project page | Video

This is an official PyTorch code repository of the paper "Point-Based Modeling of Human Clothing" (accepted to ICCV, 2021).

Setup

Build docker

  • Prerequisites: your nvidia driver should support cuda 10.2, Windows or Mac are not supported.
  • Clone repo:
    • git clone https://github.com/izakharkin/point_based_clothing.git
    • cd point_based_clothing
    • git submodule init && git submodule update
  • Docker setup:
  • Download 10_nvidia.json and place it in the docker/ folder
  • Create docker image:
    • Build on your own: run 2 commands
  • Inside the docker container: source activate pbc

Download data

  • Download the SMPL neutral model from SMPLify project page:
    • Register, go to the Downloads section, download SMPLIFY_CODE_V2.ZIP, and unpack it;
    • Move smplify_public/code/models/basicModel_neutral_lbs_10_207_0_v1.0.0.pkl to data/smpl_models/SMPL_NEUTRAL.pkl.
  • Download models checkpoints (~570 Mb): Google Drive and place them to the checkpoints/ folder;
  • Download a sample data we provide to check the appearance fitting (~480 Mb): Google Drive, unpack it, and place psp/ folder to the samples/ folder.

Run

We provide scripts for geometry fitting and inference and appearance fitting and inference.

Geometry (outfit code)

Fitting

To fit a style outfit code to a single image one can run:

python fit_outfit_code.py --config_name=outfit_code/psp

The learned outfit codes are saved to out/outfit_code/outfit_codes_<dset_name>.pkl by default. The visualization of the process is in out/outfit_code/vis_<dset_name>/:

  • Coarse fitting stage: four outfit codes initialized randomly and being optimized simultaneosly.

outfit_code_fitting_coarse

  • Fine fitting stage: mean of found outfit codes is being optimized further to possibly imrove the reconstruction.

outfit_code_fitting_fine

Note: visibility_thr hyperparameter in fit_outfit_code.py may affect the quality of result point cloud (e.f. make it more sparse). Feel free to tune it if the result seems not perfect.

vis_thr_360

Inference

outfit_code_inference

To further infer the fitted outfit style on the train or on new subjects please see infer_outfit_code.ipynb. To run jupyter notebook server from the docker, run this inside the container:

jupyter notebook --ip=0.0.0.0 --port=8087 --no-browser 

Appearance (neural descriptors)

Fitting

To fit a clothing appearance to a sequence of frames one can run:

python fit_appearance.py --config_name=appearance/psp_male-3-casual

The learned neural descriptors ntex0_<epoch>.pth and neural rendering network weights model0_<epoch>.pth are saved to out/appearance/<dset_name>/<subject_id>/<experiment_dir>/checkpoints/ by default. The visualization of the process is in out/appearance/<dset_name>/<subject_id>/<experiment_dir>/visuals/.

Inference

appearance_inference

To further infer the fitted clothing point cloud and its appearance on the train or on new subjects please see infer_appearance.ipynb. To run jupyter notebook server from the docker, run this inside the container:

jupyter notebook --ip=0.0.0.0 --port=8087 --no-browser 

Citation

If you find our work helpful, please do not hesitate to cite us:

@InProceedings{Zakharkin_2021_ICCV,
    author    = {Zakharkin, Ilya and Mazur, Kirill and Grigorev, Artur and Lempitsky, Victor},
    title     = {Point-Based Modeling of Human Clothing},
    booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
    month     = {October},
    year      = {2021},
    pages     = {14718-14727}
}

Non-commercial use only.

Related projects

We also thank the authors of Cloth3D and PeopleSnapshot datasets.

Owner
Visual Understanding Lab @ Samsung AI Center Moscow
Visual Understanding Lab @ Samsung AI Center Moscow
python 93% acc. CNN Dogs Vs Cats ( Pytorch )

English | 简体中文(测试中...敬请期待) Cnn-Classification-Dog-Vs-Cat 猫狗辨别 (pytorch版本) CNN Resnet18 的猫狗分类器,基于ResNet及其变体网路系列,对于一般的图像识别任务表现优异,模型精准度高达93%(小型样本)。 项目制作于

apple ye 1 May 22, 2022
GoodNews Everyone! Context driven entity aware captioning for news images

This is the code for a CVPR 2019 paper, called GoodNews Everyone! Context driven entity aware captioning for news images. Enjoy! Model preview: Huge T

117 Dec 19, 2022
A Semantic Segmentation Network for Urban-Scale Building Footprint Extraction Using RGB Satellite Imagery

A Semantic Segmentation Network for Urban-Scale Building Footprint Extraction Using RGB Satellite Imagery This repository is the official implementati

Aatif Jiwani 42 Dec 08, 2022
git《Joint Entity and Relation Extraction with Set Prediction Networks》(2020) GitHub:

Joint Entity and Relation Extraction with Set Prediction Networks Source code for Joint Entity and Relation Extraction with Set Prediction Networks. W

130 Dec 13, 2022
Syllabus del curso IIC2115 - Programación como Herramienta para la Ingeniería 2022/I

IIC2115 - Programación como Herramienta para la Ingeniería Videos y tutoriales Tutorial CMD Tutorial Instalación Python y Jupyter Tutorial de git-GitH

21 Nov 09, 2022
Implementation of "StrengthNet: Deep Learning-based Emotion Strength Assessment for Emotional Speech Synthesis"

StrengthNet Implementation of "StrengthNet: Deep Learning-based Emotion Strength Assessment for Emotional Speech Synthesis" https://arxiv.org/abs/2110

RuiLiu 65 Dec 20, 2022
Repo for "Physion: Evaluating Physical Prediction from Vision in Humans and Machines" submission to NeurIPS 2021 (Datasets & Benchmarks track)

Physion: Evaluating Physical Prediction from Vision in Humans and Machines This repo contains code and data to reproduce the results in our paper, Phy

Cognitive Tools Lab 38 Jan 06, 2023
[CVPR 2021] MetaSAug: Meta Semantic Augmentation for Long-Tailed Visual Recognition

MetaSAug: Meta Semantic Augmentation for Long-Tailed Visual Recognition (CVPR 2021) arXiv Prerequisite PyTorch = 1.2.0 Python3 torchvision PIL argpar

51 Nov 11, 2022
JDet is Object Detection Framework based on Jittor.

JDet is Object Detection Framework based on Jittor.

135 Dec 14, 2022
WaveFake: A Data Set to Facilitate Audio DeepFake Detection

WaveFake: A Data Set to Facilitate Audio DeepFake Detection This is the code repository for our NeurIPS 2021 (Track on Datasets and Benchmarks) paper

Chair for Sys­tems Se­cu­ri­ty 27 Dec 22, 2022
Automatic differentiation with weighted finite-state transducers.

GTN: Automatic Differentiation with WFSTs Quickstart | Installation | Documentation What is GTN? GTN is a framework for automatic differentiation with

100 Dec 29, 2022
A bare-bones TensorFlow framework for Bayesian deep learning and Gaussian process approximation

Aboleth A bare-bones TensorFlow framework for Bayesian deep learning and Gaussian process approximation [1] with stochastic gradient variational Bayes

Gradient Institute 127 Dec 12, 2022
Distributed Arcface Training in Pytorch

Distributed Arcface Training in Pytorch

3 Nov 23, 2021
Algebraic effect handlers in Python

PyEffect: Algebraic effects in Python What IDK. Usage effects.handle(operation, handlers=None) effects.set_handler(effect, handler) Supported effects

Greg Werbin 5 Dec 27, 2021
UniFormer - official implementation of UniFormer

UniFormer This repo is the official implementation of "Uniformer: Unified Transf

SenseTime X-Lab 573 Jan 04, 2023
VLG-Net: Video-Language Graph Matching Networks for Video Grounding

VLG-Net: Video-Language Graph Matching Networks for Video Grounding Introduction Official repository for VLG-Net: Video-Language Graph Matching Networ

Mattia Soldan 25 Dec 04, 2022
Efficient Lottery Ticket Finding: Less Data is More

The lottery ticket hypothesis (LTH) reveals the existence of winning tickets (sparse but critical subnetworks) for dense networks, that can be trained in isolation from random initialization to match

VITA 20 Sep 04, 2022
Implementation of Stochastic Image-to-Video Synthesis using cINNs.

Stochastic Image-to-Video Synthesis using cINNs Official PyTorch implementation of Stochastic Image-to-Video Synthesis using cINNs accepted to CVPR202

CompVis Heidelberg 135 Dec 28, 2022
ChineseBERT: Chinese Pretraining Enhanced by Glyph and Pinyin Information

ChineseBERT: Chinese Pretraining Enhanced by Glyph and Pinyin Information This repository contains code, model, dataset for ChineseBERT at ACL2021. Ch

413 Dec 01, 2022
PyTorch and GPyTorch implementation of the paper "Conditioning Sparse Variational Gaussian Processes for Online Decision-making."

Conditioning Sparse Variational Gaussian Processes for Online Decision-making This repository contains a PyTorch and GPyTorch implementation of the pa

Wesley Maddox 16 Dec 08, 2022