activity
20192022
most citedMesh Guided One-shot Face Reenactment using Graph Convolutional Networks

41 citations · 89 across the 16 of their papers we have counts for

collaborators

18 papers

cs.CV2022

Learning Implicit Body Representations from Double Diffusion Based Neural Radiance Fields

Guangming Yao, Hongzhi Wu, Yi Yuan +3

In this paper, we present a novel double diffusion based neural radiance field, dubbed DD-NeRF, to reconstruct human body geometry and render the human body appearance in novel vie…

cs.CV2021

In-game Residential Home Planning via Visual Context-aware Global Relation Learning

Lijuan Liu, Yin Yang, Yi Yuan +3

In this paper, we propose an effective global relation learning algorithm to recommend an appropriate location of a building unit for in-game customization of residential home comp…

cs.CV2021

MeInGame: Create a Game Character Face from a Single Portrait

Jiangke Lin, Yi Yuan, Zhengxia Zou

Many deep learning based 3D face reconstruction methods have been proposed recently, however, few of them have applications in games. Current game character customization systems e…

cs.CV20213 cited

Structure-aware Person Image Generation with Pose Decomposition and Semantic Correlation

Jilin Tang, Yi Yuan, Tianjia Shao +3

In this paper we tackle the problem of pose guided person image generation, which aims to transfer a person image from the source pose to a novel target pose while maintaining the…

cs.CV2021

One-shot Face Reenactment Using Appearance Adaptive Normalization

Guangming Yao, Yi Yuan, Tianjia Shao +5

The paper proposes a novel generative adversarial network for one-shot face reenactment, which can animate a single face image to a different pose-and-expression (provided by a dri…

cs.CV2020

NeuralMagicEye: Learning to See and Understand the Scene Behind an Autostereogram

Zhengxia Zou, Tianyang Shi, Yi Yuan +1

An autostereogram, a.k.a. magic eye image, is a single-image stereogram that can create visual illusions of 3D scenes from 2D textures. This paper studies an interesting question t…