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Recent geometric methods need reliable estimates of 3D motion parameters to procure accurate dense depth map of a complex dynamic scene from monocular images \cite{kumar2017monocular, ranftl2016dense}. Generally, to estimate…

Computer Vision and Pattern Recognition · Computer Science 2019-03-26 Suryansh Kumar , Ram Srivatsav Ghorakavi , Yuchao Dai , Hongdong Li

Recent progress in human shape learning, shows that neural implicit models are effective in generating 3D human surfaces from limited number of views, and even from a single RGB image. However, existing monocular approaches still struggle…

Computer Vision and Pattern Recognition · Computer Science 2024-03-20 Marco Pesavento , Yuanlu Xu , Nikolaos Sarafianos , Robert Maier , Ziyan Wang , Chun-Han Yao , Marco Volino , Edmond Boyer , Adrian Hilton , Tony Tung

This paper investigates the evaluation of dense 3D face reconstruction from a single 2D image in the wild. To this end, we organise a competition that provides a new benchmark dataset that contains 2000 2D facial images of 135 subjects as…

Computer Vision and Pattern Recognition · Computer Science 2018-04-24 Zhen-Hua Feng , Patrik Huber , Josef Kittler , Peter JB Hancock , Xiao-Jun Wu , Qijun Zhao , Paul Koppen , Matthias Rätsch

Occlusions are a common occurrence in unconstrained face images. Single image 3D reconstruction from such face images often suffers from corruption due to the presence of occlusions. Furthermore, while a plurality of 3D reconstructions is…

Computer Vision and Pattern Recognition · Computer Science 2022-04-04 Rahul Dey , Vishnu Naresh Boddeti

We propose a framework that can deform an object in a 2D image as it exists in 3D space. Most existing methods for 3D-aware image manipulation are limited to (1) only changing the global scene information or depth, or (2) manipulating an…

Computer Vision and Pattern Recognition · Computer Science 2022-03-30 Jihyun Lee , Minhyuk Sung , Hyunjin Kim , Tae-Kyun Kim

The estimation of 3D face shape from a single image must be robust to variations in lighting, head pose, expression, facial hair, makeup, and occlusions. Robustness requires a large training set of in-the-wild images, which by construction,…

Computer Vision and Pattern Recognition · Computer Science 2019-05-17 Soubhik Sanyal , Timo Bolkart , Haiwen Feng , Michael J. Black

An authentic face restoration system is becoming increasingly demanding in many computer vision applications, e.g., image enhancement, video communication, and taking portrait. Most of the advanced face restoration models can recover…

Computer Vision and Pattern Recognition · Computer Science 2023-07-19 Yang Zhao , Tingbo Hou , Yu-Chuan Su , Xuhui Jia. Yandong Li , Matthias Grundmann

Monocular facial performance capture in-the-wild is challenging due to varied capture conditions, face shapes, and expressions. Most current methods rely on linear 3D Morphable Models, which represent facial expressions independently of…

Computer Vision and Pattern Recognition · Computer Science 2025-07-14 Arthur Josi , Luiz Gustavo Hafemann , Abdallah Dib , Emeline Got , Rafael M. O. Cruz , Marc-Andre Carbonneau

One challenge that remains open in 3D deep learning is how to efficiently represent 3D data to feed deep networks. Recent works have relied on volumetric or point cloud representations, but such approaches suffer from a number of issues…

Computer Vision and Pattern Recognition · Computer Science 2019-01-25 Jhony K. Pontes , Chen Kong , Sridha Sridharan , Simon Lucey , Anders Eriksson , Clinton Fookes

This paper addresses the challenge of reconstructing an animatable human model from a multi-view video. Some recent works have proposed to decompose a non-rigidly deforming scene into a canonical neural radiance field and a set of…

Computer Vision and Pattern Recognition · Computer Science 2023-05-05 Sida Peng , Zhen Xu , Junting Dong , Qianqian Wang , Shangzhan Zhang , Qing Shuai , Hujun Bao , Xiaowei Zhou

Faces manifest large variations in many aspects, such as identity, expression, pose, and face styling. Therefore, it is a great challenge to disentangle and extract these characteristics from facial images, especially in an unsupervised…

Computer Vision and Pattern Recognition · Computer Science 2021-08-10 Jia-Ren Chang , Yong-Sheng Chen , Wei-Chen Chiu

Depth estimation is of critical interest for scene understanding and accurate 3D reconstruction. Most recent approaches in depth estimation with deep learning exploit geometrical structures of standard sharp images to predict corresponding…

Computer Vision and Pattern Recognition · Computer Science 2018-09-07 Marcela Carvalho , Bertrand Le Saux , Pauline Trouvé-Peloux , Andrés Almansa , Frédéric Champagnat

Compared with the image-based static facial expression recognition (SFER) task, the dynamic facial expression recognition (DFER) task based on video sequences is closer to the natural expression recognition scene. However, DFER is often…

Computer Vision and Pattern Recognition · Computer Science 2022-08-23 Hanting Li , Hongjing Niu , Zhaoqing Zhu , Feng Zhao

We present a real-time deep learning framework for video-based facial performance capture -- the dense 3D tracking of an actor's face given a monocular video. Our pipeline begins with accurately capturing a subject using a high-end…

Computer Vision and Pattern Recognition · Computer Science 2017-06-05 Samuli Laine , Tero Karras , Timo Aila , Antti Herva , Shunsuke Saito , Ronald Yu , Hao Li , Jaakko Lehtinen

Talking head generation is a significant research topic that still faces numerous challenges. Previous works often adopt generative adversarial networks or regression models, which are plagued by generation quality and average facial shape…

Computer Vision and Pattern Recognition · Computer Science 2024-08-20 Ziyu Yao , Xuxin Cheng , Zhiqi Huang

Muscle-based systems have the potential to provide both anatomical accuracy and semantic interpretability as compared to blendshape models; however, a lack of expressivity and differentiability has limited their impact. Thus, we propose…

Computer Vision and Pattern Recognition · Computer Science 2018-12-10 Michael Bao , Matthew Cong , Stéphane Grabli , Ronald Fedkiw

Reconstructing hand-held objects from monocular RGB images is an appealing yet challenging task. In this task, contacts between hands and objects provide important cues for recovering the 3D geometry of the hand-held objects. Though recent…

Computer Vision and Pattern Recognition · Computer Science 2024-01-17 Junxing Hu , Hongwen Zhang , Zerui Chen , Mengcheng Li , Yunlong Wang , Yebin Liu , Zhenan Sun

One-shot video-driven talking face generation aims at producing a synthetic talking video by transferring the facial motion from a video to an arbitrary portrait image. Head pose and facial expression are always entangled in facial motion…

Computer Vision and Pattern Recognition · Computer Science 2023-03-03 Youxin Pang , Yong Zhang , Weize Quan , Yanbo Fan , Xiaodong Cun , Ying Shan , Dong-ming Yan

Human avatar has become a novel type of 3D asset with various applications. Ideally, a human avatar should be fully customizable to accommodate different settings and environments. In this work, we introduce NECA, an approach capable of…

Computer Vision and Pattern Recognition · Computer Science 2024-03-18 Junjin Xiao , Qing Zhang , Zhan Xu , Wei-Shi Zheng

The ability to create realistic, animatable and relightable head avatars from casual video sequences would open up wide ranging applications in communication and entertainment. Current methods either build on explicit 3D morphable meshes…

Computer Vision and Pattern Recognition · Computer Science 2023-03-01 Yufeng Zheng , Wang Yifan , Gordon Wetzstein , Michael J. Black , Otmar Hilliges