Face Attribute Invertion

01/14/2020
by   X G Tu, et al.
0

Manipulating human facial images between two domains is an important and interesting problem. Most of the existing methods address this issue by applying two generators or one generator with extra conditional inputs. In this paper, we proposed a novel self-perception method based on GANs for automatical face attribute inverse. The proposed method takes face images as inputs and employs only one single generator without being conditioned on other inputs. Profiting from the multi-loss strategy and modified U-net structure, our model is quite stable in training and capable of preserving finer details of the original face images.

READ FULL TEXT
research
05/01/2019

Learn to synthesize and synthesize to learn

Attribute guided face image synthesis aims to manipulate attributes on a...
research
12/03/2020

Attributes Aware Face Generation with Generative Adversarial Networks

Recent studies have shown remarkable success in face image generations. ...
research
09/18/2018

Attribute Enhanced Face Aging with Wavelet-based Generative Adversarial Networks

Since it is difficult to collect face images of the same subject over a ...
research
11/12/2018

Hallucinating very low-resolution and obscured face images

Most of the face hallucination methods are often designed for complete i...
research
05/15/2018

Learning to Deblur Images with Exemplars

Human faces are one interesting object class with numerous applications....
research
09/13/2013

A Novel Approach in detecting pose orientation of a 3D face required for face

In this paper we present a novel approach that takes as input a 3D image...
research
10/04/2011

Discriminately Decreasing Discriminability with Learned Image Filters

In machine learning and computer vision, input images are often filtered...

Please sign up or login with your details

Forgot password? Click here to reset