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Digital humans and, especially, 3D facial avatars have raised a lot of attention in the past years, as they are the backbone of several applications like immersive telepresence in AR or VR. Despite the progress, facial avatars reconstructed…

Computer Vision and Pattern Recognition · Computer Science 2023-11-27 Berna Kabadayi , Wojciech Zielonka , Bharat Lal Bhatnagar , Gerard Pons-Moll , Justus Thies

Advances in face synthesis have raised alarms about the deceptive use of synthetic faces. Can synthetic identities be effectively used to fool human observers? In this paper, we introduce a study of the human perception of synthetic faces…

Computer Vision and Pattern Recognition · Computer Science 2021-11-09 Bingyu Shen , Brandon RichardWebster , Alice O'Toole , Kevin Bowyer , Walter J. Scheirer

We propose a novel end-to-end semi-supervised adversarial framework to generate photorealistic face images of new identities with wide ranges of expressions, poses, and illuminations conditioned by a 3D morphable model. Previous adversarial…

Computer Vision and Pattern Recognition · Computer Science 2020-09-09 Baris Gecer , Binod Bhattarai , Josef Kittler , Tae-Kyun Kim

We present 3DGH, an unconditional generative model for 3D human heads with composable hair and face components. Unlike previous work that entangles the modeling of hair and face, we propose to separate them using a novel data representation…

Recent advances in deep convolutional neural networks (DCNNs) have shown impressive performance improvements on thermal to visible face synthesis and matching problems. However, current DCNN-based synthesis models do not perform well on…

Computer Vision and Pattern Recognition · Computer Science 2022-01-14 Xing Di , Shuowen Hu , Vishal M. Patel

Despite the rapid progress of generative adversarial networks (GANs) in image synthesis in recent years, the existing image synthesis approaches work in either geometry domain or appearance domain alone which often introduces various…

Computer Vision and Pattern Recognition · Computer Science 2023-04-21 Fangneng Zhan , Jiaxing Huang , Shijian Lu

Synthesizing high-quality realistic images from text descriptions is a challenging task. Existing text-to-image Generative Adversarial Networks generally employ a stacked architecture as the backbone yet still remain three flaws. First, the…

Computer Vision and Pattern Recognition · Computer Science 2022-10-18 Ming Tao , Hao Tang , Fei Wu , Xiao-Yuan Jing , Bing-Kun Bao , Changsheng Xu

Audio-driven talking head generation is advancing from 2D to 3D content. Notably, Neural Radiance Field (NeRF) is in the spotlight as a means to synthesize high-quality 3D talking head outputs. Unfortunately, this NeRF-based approach…

Computer Vision and Pattern Recognition · Computer Science 2024-05-13 Gihoon Kim , Kwanggyoon Seo , Sihun Cha , Junyong Noh

Automatically generating a complete 3D scene from a text description, a reference image, or both has significant applications in fields like virtual reality and gaming. However, current methods often generate low-quality textures and…

Computer Vision and Pattern Recognition · Computer Science 2025-04-08 Zhexiao Xiong , Zhang Chen , Zhong Li , Yi Xu , Nathan Jacobs

Face sketch synthesis has made significant progress with the development of deep neural networks in these years. The delicate depiction of sketch portraits facilitates a wide range of applications like digital entertainment and law…

Computer Vision and Pattern Recognition · Computer Science 2021-06-30 Xingqun Qi , Muyi Sun , Weining Wang , Xiaoxiao Dong , Qi Li , Caifeng Shan

We propose a novel 3D deepfake generation framework based on 3D Gaussian Splatting that enables realistic, identity-preserving face swapping and reenactment in a fully controllable 3D space. Compared to conventional 2D deepfake approaches…

Computer Vision and Pattern Recognition · Computer Science 2025-09-16 Wending Liu , Siyun Liang , Huy H. Nguyen , Isao Echizen

Recent advances in deep generative models have led to immense progress in 3D shape synthesis. While existing models are able to synthesize shapes represented as voxels, point-clouds, or implicit functions, these methods only indirectly…

Computer Vision and Pattern Recognition · Computer Science 2022-01-04 Andrew Luo , Tianqin Li , Wen-Hao Zhang , Tai Sing Lee

Creating controllable, photorealistic, and geometrically detailed digital doubles of real humans solely from video data is a key challenge in Computer Graphics and Vision, especially when real-time performance is required. Recent methods…

Computer Vision and Pattern Recognition · Computer Science 2023-12-11 Heming Zhu , Fangneng Zhan , Christian Theobalt , Marc Habermann

Face synthesis is an important problem in computer vision with many applications. In this work, we describe a new method, namely LandmarkGAN, to synthesize faces based on facial landmarks as input. Facial landmarks are a natural, intuitive,…

Computer Vision and Pattern Recognition · Computer Science 2021-02-09 Pu Sun , Yuezun Li , Honggang Qi , Siwei Lyu

Recent years have seen remarkable progress in deep learning powered visual content creation. This includes deep generative 3D-aware image synthesis, which produces high-idelity images in a 3D-consistent manner while simultaneously capturing…

Computer Vision and Pattern Recognition · Computer Science 2023-10-04 Weihao Xia , Jing-Hao Xue

A promise of Generative Adversarial Networks (GANs) is to provide cheap photorealistic data for training and validating AI models in autonomous driving. Despite their huge success, their performance on complex images featuring multiple…

Computer Vision and Pattern Recognition · Computer Science 2023-05-17 George Eskandar , Youssef Farag , Tarun Yenamandra , Daniel Cremers , Karim Guirguis , Bin Yang

Recent breakthroughs in single-image 3D portrait reconstruction have enabled telepresence systems to stream 3D portrait videos from a single camera in real-time, potentially democratizing telepresence. However, per-frame 3D reconstruction…

Computer Vision and Pattern Recognition · Computer Science 2024-05-03 Shengze Wang , Xueting Li , Chao Liu , Matthew Chan , Michael Stengel , Josef Spjut , Henry Fuchs , Shalini De Mello , Koki Nagano

In the field of computer vision, unsupervised learning for 2D object generation has advanced rapidly in the past few years. However, 3D object generation has not garnered the same attention or success as its predecessor. To facilitate novel…

Computer Vision and Pattern Recognition · Computer Science 2020-07-29 Devendra K. Jangid , Neal R. Brodnik , Amil Khan , McLean P. Echlin , Tresa M. Pollock , Sam Daly , B. S. Manjunath

To bring digital avatars into people's lives, it is highly demanded to efficiently generate complete, realistic, and animatable head avatars. This task is challenging, and it is difficult for existing methods to satisfy all the requirements…

Computer Vision and Pattern Recognition · Computer Science 2023-04-11 Sijing Wu , Yichao Yan , Yunhao Li , Yuhao Cheng , Wenhan Zhu , Ke Gao , Xiaobo Li , Guangtao Zhai

Talking head generation aims to generate faces that maintain the identity information of the source image and imitate the motion of the driving image. Most pioneering methods rely primarily on 2D representations and thus will inevitably…

Computer Vision and Pattern Recognition · Computer Science 2023-04-12 Weichuang Li , Longhao Zhang , Dong Wang , Bin Zhao , Zhigang Wang , Mulin Chen , Bang Zhang , Zhongjian Wang , Liefeng Bo , Xuelong Li