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We propose an approach to 3D reconstruction via inverse procedural modeling and investigate two variants of this approach. The first option consists in the fitting set of input parameters using a genetic algorithm. We demonstrate the…

Graphics · Computer Science 2023-10-23 Albert Garifullin , Nikolay Maiorov , Vladimir Frolov

3D face reconstruction plays a very important role in many real-world multimedia applications, including digital entertainment, social media, affection analysis, and person identification. The de-facto pipeline for estimating the parametric…

Computer Vision and Pattern Recognition · Computer Science 2021-01-07 Jialiang Zhang , Lixiang Lin , Jianke Zhu , Steven C. H. Hoi

In this work, we present a new method for 3D face reconstruction from sparse-view RGB images. Unlike previous methods which are built upon 3D morphable models (3DMMs) with limited details, we leverage an implicit representation to encode…

Computer Vision and Pattern Recognition · Computer Science 2022-10-04 Moran Li , Haibin Huang , Yi Zheng , Mengtian Li , Nong Sang , Chongyang Ma

This paper presents a novel framework to recover \emph{detailed} avatar from a single image. It is a challenging task due to factors such as variations in human shapes, body poses, texture, and viewpoints. Prior methods typically attempt to…

Computer Vision and Pattern Recognition · Computer Science 2021-08-21 Hao Zhu , Xinxin Zuo , Haotian Yang , Sen Wang , Xun Cao , Ruigang Yang

The task of reconstructing detailed 3D human body models from images is interesting but challenging in computer vision due to the high freedom of human bodies. In order to tackle the problem, we propose a coarse-to-fine method to…

Computer Vision and Pattern Recognition · Computer Science 2020-12-14 Zhongguo Li , Magnus Oskarsson , Anders Heyden

Videos can be manipulated by duplicating a sequence of consecutive frames with the goal of concealing or imitating a specific content in the same video. In this paper, we propose a novel coarse-to-fine framework based on deep Convolutional…

Computer Vision and Pattern Recognition · Computer Science 2019-05-07 Chengjiang Long , Arslan Basharat , Anthony Hoogs

Aiming at inferring 3D shapes from 2D images, 3D shape reconstruction has drawn huge attention from researchers in computer vision and deep learning communities. However, it is not practical to assume that 2D input images and their…

Computer Vision and Pattern Recognition · Computer Science 2018-11-30 Yi-Lun Liao , Yao-Cheng Yang , Yu-Chiang Frank Wang

Over many decades, researchers working in object recognition have longed for an end-to-end automated system that will simply accept 2D or 3D image or videos as inputs and output the labels of objects in the input data. Computer vision…

Computer Vision and Pattern Recognition · Computer Science 2016-01-29 Rama Chellappa , Jun-Cheng Chen , Rajeev Ranjan , Swami Sankaranarayanan , Amit Kumar , Vishal M. Patel , Carlos D. Castillo

Face recognition has been of great importance in many applications as a biometric for its throughput, convenience, and non-invasiveness. Recent advancements in deep Convolutional Neural Network (CNN) architectures have boosted significantly…

Computer Vision and Pattern Recognition · Computer Science 2020-10-01 Zhiqian You , Tingting Yang , Miao Jin

Indirect image registration is a promising technique to improve image reconstruction quality by providing a shape prior for the reconstruction task. In this paper, we propose a novel hybrid method that seeks to reconstruct high quality…

Image and Video Processing · Electrical Eng. & Systems 2019-12-18 Jiulong Liu , Angelica I. Aviles-Rivero , Hui Ji , Carola-Bibiane Schönlieb

We propose an end-to-end deep learning architecture that produces a 3D shape in triangular mesh from a single color image. Limited by the nature of deep neural network, previous methods usually represent a 3D shape in volume or point cloud,…

Computer Vision and Pattern Recognition · Computer Science 2018-08-06 Nanyang Wang , Yinda Zhang , Zhuwen Li , Yanwei Fu , Wei Liu , Yu-Gang Jiang

Heterogeneous face recognition between color image and depth image is a much desired capacity for real world applications where shape information is looked upon as merely involved in gallery. In this paper, we propose a cross-modal deep…

Computer Vision and Pattern Recognition · Computer Science 2017-09-15 Wuming Zhang , Zhixin Shu , Dimitris Samaras , Liming Chen

3D Morphable Model (3DMM) based methods have achieved great success in recovering 3D face shapes from single-view images. However, the facial textures recovered by such methods lack the fidelity as exhibited in the input images. Recent work…

Computer Vision and Pattern Recognition · Computer Science 2020-07-14 Jiangke Lin , Yi Yuan , Tianjia Shao , Kun Zhou

A lot of work has been done towards reconstructing the 3D facial structure from single images by capitalizing on the power of Deep Convolutional Neural Networks (DCNNs). In the recent works, the texture features either correspond to…

Computer Vision and Pattern Recognition · Computer Science 2022-03-28 Baris Gecer , Stylianos Ploumpis , Irene Kotsia , Stefanos Zafeiriou

Previous face inverse rendering methods often require synthetic data with ground truth and/or professional equipment like a lighting stage. However, a model trained on synthetic data or using pre-defined lighting priors is typically unable…

Computer Vision and Pattern Recognition · Computer Science 2023-01-31 Meng Wang , Xiaojie Guo , Wenjing Dai , Jiawan Zhang

We present an unsupervised approach for learning to estimate three dimensional (3D) facial structure from a single image while also predicting 3D viewpoint transformations that match a desired pose and facial geometry. We achieve this by…

Computer Vision and Pattern Recognition · Computer Science 2018-12-27 Joel Ruben Antony Moniz , Christopher Beckham , Simon Rajotte , Sina Honari , Christopher Pal

Although deep learning has yielded impressive performance for face recognition, many studies have shown that different networks learn different feature maps: while some networks are more receptive to pose and illumination others appear to…

Computer Vision and Pattern Recognition · Computer Science 2017-02-16 Navaneeth Bodla , Jingxiao Zheng , Hongyu Xu , Jun-Cheng Chen , Carlos Castillo , Rama Chellappa

We propose a straightforward method that simultaneously reconstructs the 3D facial structure and provides dense alignment. To achieve this, we design a 2D representation called UV position map which records the 3D shape of a complete face…

Computer Vision and Pattern Recognition · Computer Science 2018-03-22 Yao Feng , Fan Wu , Xiaohu Shao , Yanfeng Wang , Xi Zhou

Recently, 3D face reconstruction and face alignment tasks are gradually combined into one task: 3D dense face alignment. Its goal is to reconstruct the 3D geometric structure of face with pose information. In this paper, we propose a graph…

Computer Vision and Pattern Recognition · Computer Science 2019-04-12 Huawei Wei , Shuang Liang , Yichen Wei

Inferring the 3D shape of an object from an RGB image has shown impressive results, however, existing methods rely primarily on recognizing the most similar 3D model from the training set to solve the problem. These methods suffer from poor…

Computer Vision and Pattern Recognition · Computer Science 2019-10-22 Haozhe Xie , Hongxun Yao , Shangchen Zhou , Shengping Zhang , Xiaoshuai Sun , Wenxiu Sun