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Related papers: High-Quality Real Time Facial Capture Based on Sin…

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In this paper, we present a large-scale detailed 3D face dataset, FaceScape, and the corresponding benchmark to evaluate single-view facial 3D reconstruction. By training on FaceScape data, a novel algorithm is proposed to predict elaborate…

Computer Vision and Pattern Recognition · Computer Science 2023-09-19 Hao Zhu , Haotian Yang , Longwei Guo , Yidi Zhang , Yanru Wang , Mingkai Huang , Menghua Wu , Qiu Shen , Ruigang Yang , Xun Cao

Recent advancements in human video synthesis have enabled the generation of high-quality videos through the application of stable diffusion models. However, existing methods predominantly concentrate on animating solely the human element…

Computer Vision and Pattern Recognition · Computer Science 2024-05-29 Jinlin Liu , Kai Yu , Mengyang Feng , Xiefan Guo , Miaomiao Cui

Performing facial expression transfer under one-shot setting has been increasing in popularity among research community with a focus on precise control of expressions. Existing techniques showcase compelling results in perceiving…

Computer Vision and Pattern Recognition · Computer Science 2024-04-24 Siddharth Nijhawan , Takuya Yashima , Tamaki Kojima

In response to the global COVID-19 pandemic, there has been a critical demand for protective measures, with face masks emerging as a primary safeguard. The approach involves a two-fold strategy: first, recognizing the presence of a face by…

Computer Vision and Pattern Recognition · Computer Science 2023-11-20 R. Chinnaiyan , Iyyappan M , Al Raiyan Shariff A , Kondaveeti Sai , Mallikarjunaiah B M , P Bharath

Readily editable mesh blendshapes have been widely used in animation pipelines, while recent advancements in neural geometry and appearance representations have enabled high-quality inverse rendering. Building upon these observations, we…

Graphics · Computer Science 2024-08-21 Xin Ming , Jiawei Li , Jingwang Ling , Libo Zhang , Feng Xu

We present a novel learning-based framework for face reenactment. The proposed method, known as ReenactGAN, is capable of transferring facial movements and expressions from monocular video input of an arbitrary person to a target person.…

Computer Vision and Pattern Recognition · Computer Science 2018-07-31 Wayne Wu , Yunxuan Zhang , Cheng Li , Chen Qian , Chen Change Loy

Limited annotated data available for the recognition of facial expression and action units embarrasses the training of deep networks, which can learn disentangled invariant features. However, a linear model with just several parameters…

Computer Vision and Pattern Recognition · Computer Science 2017-01-16 Xiang Xiang , Trac D. Tran

In this paper, we propose a novel text-based talking-head video generation framework that synthesizes high-fidelity facial expressions and head motions in accordance with contextual sentiments as well as speech rhythm and pauses. To be…

Computer Vision and Pattern Recognition · Computer Science 2021-05-10 Lincheng Li , Suzhen Wang , Zhimeng Zhang , Yu Ding , Yixing Zheng , Xin Yu , Changjie Fan

With rapid advancements in generative modeling, deepfake techniques are increasingly narrowing the gap between real and synthetic videos, raising serious privacy and security concerns. Beyond traditional face swapping and reenactment, an…

Computer Vision and Pattern Recognition · Computer Science 2025-04-15 Tharun Anand , Siva Sankar Sajeev , Pravin Nair

In the last few years, several techniques for facial manipulation in videos have been successfully developed and made available to the masses (i.e., FaceSwap, deepfake, etc.). These methods enable anyone to easily edit faces in video…

Computer Vision and Pattern Recognition · Computer Science 2020-04-17 Nicolò Bonettini , Edoardo Daniele Cannas , Sara Mandelli , Luca Bondi , Paolo Bestagini , Stefano Tubaro

Talking head generation is to generate video based on a given source identity and target motion. However, current methods face several challenges that limit the quality and controllability of the generated videos. First, the generated face…

Computer Vision and Pattern Recognition · Computer Science 2023-11-03 Yue Gao , Yuan Zhou , Jinglu Wang , Xiao Li , Xiang Ming , Yan Lu

Frame-level visual features are generally aggregated in time with the techniques such as LSTM, Fisher Vectors, NetVLAD etc. to produce a robust video-level representation. We here introduce a learnable aggregation technique whose primary…

Computer Vision and Pattern Recognition · Computer Science 2017-08-25 Savas Ozkan , Gozde Bozdagi Akar

Video-based human motion transfer creates video animations of humans following a source motion. Current methods show remarkable results for tightly-clad subjects. However, the lack of temporally consistent handling of plausible clothing…

Computer Vision and Pattern Recognition · Computer Science 2020-12-22 Moritz Kappel , Vladislav Golyanik , Mohamed Elgharib , Jann-Ole Henningson , Hans-Peter Seidel , Susana Castillo , Christian Theobalt , Marcus Magnor

We introduce a novel framework for continuous facial motion deblurring that restores the continuous sharp moment latent in a single motion-blurred face image via a moment control factor. Although a motion-blurred image is the accumulated…

Computer Vision and Pattern Recognition · Computer Science 2022-07-15 Tae Bok Lee , Sujy Han , Yong Seok Heo

Automated Facial Expression Recognition (FER) has been a challenging task for decades. Many of the existing works use hand-crafted features such as LBP, HOG, LPQ, and Histogram of Optical Flow (HOF) combined with classifiers such as Support…

Computer Vision and Pattern Recognition · Computer Science 2020-04-17 Behzad Hasani , Mohammad H. Mahoor

In this paper we present a new deep learning-driven approach to image-based synthesis of animations involving humanoid characters. Unlike previous deep approaches to image-based animation our method makes no assumptions on the type of…

Graphics · Computer Science 2019-08-14 John Kanji , David I. W. Levin

The rise of deepfake technology brings forth new questions about the authenticity of various forms of media found online today. Videos and images generated by artificial intelligence (AI) have become increasingly more difficult to…

Computer Vision and Pattern Recognition · Computer Science 2025-07-28 Benjamin Carter , Nathan Dilla , Micheal Callahan , Atuhaire Ambala

We present a single-image 3D face synthesis technique that can handle challenging facial expressions while recovering fine geometric details. Our technique employs expression analysis for proxy face geometry generation and combines…

Computer Vision and Pattern Recognition · Computer Science 2019-12-04 Anpei Chen , Zhang Chen , Guli Zhang , Ziheng Zhang , Kenny Mitchell , Jingyi Yu

Existing methods achieve high-quality facial albedo capture under controllable lighting, which increases capture cost and limits usability. We propose WildCap, a novel method for high-quality facial albedo capture from a smartphone video…

Computer Vision and Pattern Recognition · Computer Science 2026-03-18 Yuxuan Han , Xin Ming , Tianxiao Li , Zhuofan Shen , Qixuan Zhang , Lan Xu , Feng Xu

We present a unique system for large-scale, multi-performer, high resolution 4D volumetric capture providing realistic free-viewpoint video up to and including 4K resolution facial closeups. To achieve this, we employ a novel volumetric…

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