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
Balancing Principle for Unsupervised Domain Adaptation

Blancing Principle for Domain Adaptation NeurIPS 2021 Paper Abstract We address the unsolved algorithm design problem of choosing a justified regulari

Marius-Constantin Dinu 4 Dec 15, 2022
This package implements THOR: Transformer with Stochastic Experts.

THOR: Transformer with Stochastic Experts This PyTorch package implements Taming Sparsely Activated Transformer with Stochastic Experts. Installation

Microsoft 45 Nov 22, 2022
Code for "Graph-Evolving Meta-Learning for Low-Resource Medical Dialogue Generation". [AAAI 2021]

Graph Evolving Meta-Learning for Low-resource Medical Dialogue Generation Code to be further cleaned... This repo contains the code of the following p

Shuai Lin 29 Nov 01, 2022
A Deep learning based streamlit web app which can tell with which bollywood celebrity your face resembles.

Project Name: Which Bollywood Celebrity You look like A Deep learning based streamlit web app which can tell with which bollywood celebrity your face

BAPPY AHMED 20 Dec 28, 2021
Neural models of common sense. 🤖

Unicorn on Rainbow Neural models of common sense. This repository is for the paper: Unicorn on Rainbow: A Universal Commonsense Reasoning Model on a N

AI2 60 Jan 05, 2023
Python Environment for Bayesian Learning

Pebl is a python library and command line application for learning the structure of a Bayesian network given prior knowledge and observations. Pebl in

Abhik Shah 103 Jul 14, 2022
HyperLib: Deep learning in the Hyperbolic space

HyperLib: Deep learning in the Hyperbolic space Background This library implements common Neural Network components in the hypberbolic space (using th

105 Dec 25, 2022
RipsNet: a general architecture for fast and robust estimation of the persistent homology of point clouds

RipsNet: a general architecture for fast and robust estimation of the persistent homology of point clouds This repository contains the code asscoiated

Felix Hensel 14 Dec 12, 2022
Negative Interactions for Improved Collaborative Filtering:

Negative Interactions for Improved Collaborative Filtering: Don’t go Deeper, go Higher This notebook provides an implementation in Python 3 of the alg

Harald Steck 21 Mar 05, 2022
Real time sign language recognition

The proposed work aims at converting american sign language gestures into English that can be understood by everyone in real time.

Mohit Kaushik 6 Jun 13, 2022
The code for two papers: Feedback Transformer and Expire-Span.

transformer-sequential This repo contains the code for two papers: Feedback Transformer Expire-Span The training code is structured for long sequentia

Facebook Research 125 Dec 25, 2022
This toolkit provides codes to download and pre-process the SLUE datasets, train the baseline models, and evaluate SLUE tasks.

slue-toolkit We introduce Spoken Language Understanding Evaluation (SLUE) benchmark. This toolkit provides codes to download and pre-process the SLUE

ASAPP Research 39 Sep 21, 2022
A little software to generate and save Julia or Mandelbrot's Fractals.

Julia-Mandelbrot-s-Fractals A little software to generate and save Julia or Mandelbrot's Fractals. Dependencies : Python 3.7 or more. (Also possible t

Olivier 0 Jul 09, 2022
TensorFlow-based neural network library

Sonnet Documentation | Examples Sonnet is a library built on top of TensorFlow 2 designed to provide simple, composable abstractions for machine learn

DeepMind 9.5k Jan 07, 2023
Linear algebra python - Number of operations and problems in Linear Algebra and Numerical Linear Algebra

Linear algebra in python Number of operations and problems in Linear Algebra and

Alireza 5 Oct 09, 2022
Adaptive Denoising Training (ADT) for Recommendation.

DenoisingRec Adaptive Denoising Training for Recommendation. This is the pytorch implementation of our paper at WSDM 2021: Denoising Implicit Feedback

Wenjie Wang 51 Dec 30, 2022
[ICCV21] Self-Calibrating Neural Radiance Fields

Self-Calibrating Neural Radiance Fields, ICCV, 2021 Project Page | Paper | Video Author Information Yoonwoo Jeong [Google Scholar] Seokjun Ahn [Google

381 Dec 30, 2022
Weak-supervised Visual Geo-localization via Attention-based Knowledge Distillation

Weak-supervised Visual Geo-localization via Attention-based Knowledge Distillation Introduction WAKD is a PyTorch implementation for our ICPR-2022 pap

2 Oct 20, 2022
Codebase to experiment with a hybrid Transformer that combines conditional sequence generation with regression

Regression Transformer Codebase to experiment with a hybrid Transformer that combines conditional sequence generation with regression . Development se

International Business Machines 27 Jan 05, 2023
[CVPR 2016] Unsupervised Feature Learning by Image Inpainting using GANs

Context Encoders: Feature Learning by Inpainting CVPR 2016 [Project Website] [Imagenet Results] Sample results on held-out images: This is the trainin

Deepak Pathak 829 Dec 31, 2022