Search Results for author: Jichao Zhang

Found 9 papers, 8 papers with code

Training and Tuning Generative Neural Radiance Fields for Attribute-Conditional 3D-Aware Face Generation

1 code implementation26 Aug 2022 Jichao Zhang, Aliaksandr Siarohin, Yahui Liu, Hao Tang, Nicu Sebe, Wei Wang

To this end, we introduce a conditional GNeRF model that uses specific attribute labels as input in order to improve the controllabilities and disentangling abilities of 3D-aware generative models.

Disentanglement Face Generation

Unsupervised High-Resolution Portrait Gaze Correction and Animation

1 code implementation1 Jul 2022 Jichao Zhang, Jingjing Chen, Hao Tang, Enver Sangineto, Peng Wu, Yan Yan, Nicu Sebe, Wei Wang

Solving this problem using an unsupervised method remains an open problem, especially for high-resolution face images in the wild, which are not easy to annotate with gaze and head pose labels.

Image Inpainting

3D-Aware Semantic-Guided Generative Model for Human Synthesis

1 code implementation2 Dec 2021 Jichao Zhang, Enver Sangineto, Hao Tang, Aliaksandr Siarohin, Zhun Zhong, Nicu Sebe, Wei Wang

However, they usually struggle to generate high-quality images representing non-rigid objects, such as the human body, which is of a great interest for many computer graphics applications.

3D-Aware Image Synthesis

Controllable Person Image Synthesis with Spatially-Adaptive Warped Normalization

1 code implementation31 May 2021 Jichao Zhang, Aliaksandr Siarohin, Hao Tang, Jingjing Chen, Enver Sangineto, Wei Wang, Nicu Sebe

Controllable person image generation aims to produce realistic human images with desirable attributes (e. g., the given pose, cloth textures or hair style).

Image-to-Image Translation Pose Transfer +1

Dual In-painting Model for Unsupervised Gaze Correction and Animation in the Wild

1 code implementation9 Aug 2020 Jichao Zhang, Jingjing Chen, Hao Tang, Wei Wang, Yan Yan, Enver Sangineto, Nicu Sebe

In this paper we address the problem of unsupervised gaze correction in the wild, presenting a solution that works without the need for precise annotations of the gaze angle and the head pose.

PA-GAN: Progressive Attention Generative Adversarial Network for Facial Attribute Editing

3 code implementations12 Jul 2020 Zhenliang He, Meina Kan, Jichao Zhang, Shiguang Shan

Facial attribute editing aims to manipulate attributes on the human face, e. g., adding a mustache or changing the hair color.

Coarse-to-Fine Gaze Redirection with Numerical and Pictorial Guidance

1 code implementation7 Apr 2020 Jingjing Chen, Jichao Zhang, Enver Sangineto, Jiayuan Fan, Tao Chen, Nicu Sebe

In this paper, we propose to alleviate these problems by means of a novel gaze redirection framework which exploits both a numerical and a pictorial direction guidance, jointly with a coarse-to-fine learning strategy.

gaze redirection Image Generation

GazeCorrection:Self-Guided Eye Manipulation in the wild using Self-Supervised Generative Adversarial Networks

no code implementations arXiv 2019 Jichao Zhang, Meng Sun, Jingjing Chen, Hao Tang, Yan Yan, Xueying Qin, Nicu Sebe

Gaze correction aims to redirect the person's gaze into the camera by manipulating the eye region, and it can be considered as a specific image resynthesis problem.

Resynthesis

Sparsely Grouped Multi-task Generative Adversarial Networks for Facial Attribute Manipulation

2 code implementations19 May 2018 Jichao Zhang, Yezhi Shu, Songhua Xu, Gongze Cao, Fan Zhong, Meng Liu, Xueying Qin

To overcome such a key limitation, we propose Sparsely Grouped Generative Adversarial Networks (SG-GAN) as a novel approach that can translate images on sparsely grouped datasets where only a few samples for training are labelled.

Image-to-Image Translation Multi-Task Learning +2

Cannot find the paper you are looking for? You can Submit a new open access paper.