Toward Spatially Unbiased Generative Models (ICCV 2021)

Overview

Toward Spatially Unbiased Generative Models

Implementation of Toward Spatially Unbiased Generative Models (ICCV 2021)

Overview

Recent image generation models show remarkable generation performance. However, they mirror strong location preference in datasets, which we call spatial bias. Therefore, generators render poor samples at unseen locations and scales. We argue that the generators rely on their implicit positional encoding to render spatial content. From our observations, the generator’s implicit positional encoding is translation-variant, making the generator spatially biased. To address this issue, we propose injecting explicit positional encoding at each scale of the generator. By learning the spatially unbiased generator, we facilitate the robust use of generators in multiple tasks, such as GAN inversion, multi-scale generation, generation of arbitrary sizes and aspect ratios. Furthermore, we show that our method can also be applied to denoising diffusion probabilistic models.

Generation

Due to spatial bias, samples of the original GAN are either destructive or stuck to the center when generating from a shifted location.

Original StyleGAN2 MS-PE + StyleGAN2
a b
c d

GAN Inversion

Input Original StyleGAN2 MS-PE + StyleGAN2
e f g

Requirements

I have tested on:

  • PyTorch 1.7

Usage

Dataset

Create lmdb datasets:

python prepare_data.py --out LMDB_PATH --n_worker N_WORKER --size SIZE1,SIZE2,SIZE3,... DATASET_PATH

This will convert images to jpeg and pre-resizes it. This implementation does not use progressive growing, but you can create multiple resolution datasets using size arguments with comma separated lists, for the cases that you want to try another resolutions later.

Training

python train.py --name EXPERIMENT_NAME --path LMDB_PATH --position mspe

Set position to "none" for original StyleGAN2.

Generation

python generate.py --name EXPERIMENT_NAME --ckpt 550000.pt --truncation 1.0 --position mspe

GAN inversion

python projector.py --name EXPERIMENT_NAME --w_plus --ckpt 550000.pt --position mspe ref_face/00006.png

Notice

Because the current FFHQ dataset is tightly cropped, we used circular translation for proof-of-concept. Therefore, our samples show reflection artifacts at the boundaries. We are looking forward to training on FFHQ-U from alias-free GAN (https://arxiv.org/abs/2106.12423).

Acknowledgement

This code rely heavily on: https://github.com/rosinality/stylegan2-pytorch

Owner
Jooyoung Choi
Deep Generative Models
Jooyoung Choi
Predicting Student Attentiveness using OpenCV

Predicting-Student-Attentiveness-using-OpenCV The model will predict if a student is attentive or not through facial parameter received through the st

Johann Pinto 2 Aug 20, 2022
EgGateWayGetShell py脚本

EgGateWayGetShell_py 免责声明 由于传播、利用此文所提供的信息而造成的任何直接或者间接的后果及损失,均由使用者本人负责,作者不为此承担任何责任。 使用 python3 eg.py urls.txt 目标 title:锐捷网络-EWEB网管系统 port:4430 漏洞成因 ?p

榆木 61 Nov 09, 2022
This is a Pytorch implementation of paper: DropEdge: Towards Deep Graph Convolutional Networks on Node Classification

DropEdge: Towards Deep Graph Convolutional Networks on Node Classification This is a Pytorch implementation of paper: DropEdge: Towards Deep Graph Con

401 Dec 16, 2022
ICCV2021 - A New Journey from SDRTV to HDRTV.

ICCV2021 - A New Journey from SDRTV to HDRTV.

XyChen 82 Dec 27, 2022
Code and data of the ACL 2021 paper: Few-Shot Text Ranking with Meta Adapted Synthetic Weak Supervision

MetaAdaptRank This repository provides the implementation of meta-learning to reweight synthetic weak supervision data described in the paper Few-Shot

THUNLP 5 Jun 16, 2022
ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation

ENet in Caffe Execution times and hardware requirements Network 1024x512 1280x720 Parameters Model size (fp32) ENet 20.4 ms 32.9 ms 0.36 M 1.5 MB SegN

Timo Sämann 561 Jan 04, 2023
Continuous Conditional Random Field Convolution for Point Cloud Segmentation

CRFConv This repository is the implementation of "Continuous Conditional Random Field Convolution for Point Cloud Segmentation" 1. Setup 1) Building c

Fei Yang 8 Dec 08, 2022
Deep ViT Features as Dense Visual Descriptors

dino-vit-features [paper] [project page] Official implementation of the paper "Deep ViT Features as Dense Visual Descriptors". We demonstrate the effe

Shir Amir 113 Dec 24, 2022
Videocaptioning.pytorch - A simple implementation of video captioning

pytorch implementation of video captioning recommend installing pytorch and pyth

Yiyu Wang 2 Jan 01, 2022
Radar-to-Lidar: Heterogeneous Place Recognition via Joint Learning

radar-to-lidar-place-recognition This page is the coder of a pre-print, implemented by PyTorch. If you have some questions on this project, please fee

Huan Yin 37 Oct 09, 2022
Nvdiffrast - Modular Primitives for High-Performance Differentiable Rendering

Nvdiffrast – Modular Primitives for High-Performance Differentiable Rendering Modular Primitives for High-Performance Differentiable Rendering Samuli

NVIDIA Research Projects 675 Jan 06, 2023
Open source Python implementation of the HDR+ photography pipeline

hdrplus-python Open source Python implementation of the HDR+ photography pipeline, originally developped by Google and presented in a 2016 article. Th

77 Jan 05, 2023
Breast Cancer Classification Model is applied on a different dataset

Breast Cancer Classification Model is applied on a different dataset

1 Feb 04, 2022
Code base for reproducing results of I.Schubert, D.Driess, O.Oguz, and M.Toussaint: Learning to Execute: Efficient Learning of Universal Plan-Conditioned Policies in Robotics. NeurIPS (2021)

Learning to Execute (L2E) Official code base for completely reproducing all results reported in I.Schubert, D.Driess, O.Oguz, and M.Toussaint: Learnin

3 May 18, 2022
ComputerVision - This repository aims at realized easy network architecture

ComputerVision This repository aims at realized easy network architecture Colori

DongDong 4 Dec 14, 2022
Tensorflow-Project-Template - A best practice for tensorflow project template architecture.

Tensorflow Project Template A simple and well designed structure is essential for any Deep Learning project, so after a lot of practice and contributi

Mahmoud G. Salem 3.6k Dec 22, 2022
A PyTorch implementation of Multi-digit Number Recognition from Street View Imagery using Deep Convolutional Neural Networks

SVHNClassifier-PyTorch A PyTorch implementation of Multi-digit Number Recognition from Street View Imagery using Deep Convolutional Neural Networks If

Potter Hsu 182 Jan 03, 2023
[CVPR2021 Oral] FFB6D: A Full Flow Bidirectional Fusion Network for 6D Pose Estimation.

FFB6D This is the official source code for the CVPR2021 Oral work, FFB6D: A Full Flow Biderectional Fusion Network for 6D Pose Estimation. (Arxiv) Tab

Yisheng (Ethan) He 201 Dec 28, 2022
PRTR: Pose Recognition with Cascade Transformers

PRTR: Pose Recognition with Cascade Transformers Introduction This repository is the official implementation for Pose Recognition with Cascade Transfo

mlpc-ucsd 133 Dec 30, 2022
This repository contains a Ruby API for utilizing TensorFlow.

tensorflow.rb Description This repository contains a Ruby API for utilizing TensorFlow. Linux CPU Linux GPU PIP Mac OS CPU Not Configured Not Configur

somatic labs 825 Dec 26, 2022