Semi-parametric Image Inpainting

07/08/2018
by   Karim Iskakov, et al.
0

This paper introduces a semi-parametric approach to image inpainting for irregular holes. The nonparametric part consists of an external image database. During test time database is used to retrieve a supplementary image, similar to the input masked picture, and utilize it as auxiliary information for the deep neural network. Further, we propose a novel method of generating masks with irregular holes and present public dataset with such masks. Experiments on CelebA-HQ dataset show that our semi-parametric method yields more realistic results than previous approaches, which is confirmed by the user study.

READ FULL TEXT

page 1

page 2

page 4

page 6

research
07/12/2022

Shape-Aware Masking for Inpainting in Medical Imaging

Inpainting has recently been proposed as a successful deep learning tech...
research
04/29/2018

Semi-parametric Image Synthesis

We present a semi-parametric approach to photographic image synthesis fr...
research
08/25/2022

Unbiased Multi-Modality Guidance for Image Inpainting

Image inpainting is an ill-posed problem to recover missing or damaged i...
research
07/09/2020

A Benchmark for Inpainting of Clothing Images with Irregular Holes

Fashion image understanding is an active research field with a large num...
research
02/16/2021

Restore from Restored: Single-image Inpainting

Recent image inpainting methods show promising results due to the power ...
research
05/14/2022

SaiNet: Stereo aware inpainting behind objects with generative networks

In this work, we present an end-to-end network for stereo-consistent ima...
research
09/01/2022

Visual Prompting via Image Inpainting

How does one adapt a pre-trained visual model to novel downstream tasks ...

Please sign up or login with your details

Forgot password? Click here to reset