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Image generating neural networks are mostly viewed as black boxes, where any change in the input can have a number of globally effective changes on the output. In this work, we propose a method for learning disentangled representations to…

Computer Vision and Pattern Recognition · Computer Science 2019-08-27 Maren Awiszus , Hanno Ackermann , Bodo Rosenhahn

Photo collage aims to automatically arrange multiple photos on a given canvas with high aesthetic quality. Existing methods are based mainly on handcrafted feature optimization, which cannot adequately capture high-level human aesthetic…

Computer Vision and Pattern Recognition · Computer Science 2021-10-20 Mingrui Zhang , Mading Li , Li Chen , Jiahao Yu

Clustering is one of the fundamental tasks in computer vision and pattern recognition. Recently, deep clustering methods (algorithms based on deep learning) have attracted wide attention with their impressive performance. Most of these…

Computer Vision and Pattern Recognition · Computer Science 2021-06-14 Yanhai Gan , Xinghui Dong , Huiyu Zhou , Feng Gao , Junyu Dong

The image synthesis technique is relatively well established which can generate facial images that are indistinguishable even by human beings. However, all of these approaches uses gradients to condition the output, resulting in the…

Computer Vision and Pattern Recognition · Computer Science 2021-10-25 Feng Liu , HanYang Wang , Jiahao Zhang , Ziwang Fu , Aimin Zhou , Jiayin Qi , Zhibin Li

We present a method for synthesizing a frontal, neutral-expression image of a person's face given an input face photograph. This is achieved by learning to generate facial landmarks and textures from features extracted from a…

Computer Vision and Pattern Recognition · Computer Science 2017-10-18 Forrester Cole , David Belanger , Dilip Krishnan , Aaron Sarna , Inbar Mosseri , William T. Freeman

This paper explores a novel approach to model strategies for flattening wrinkled cloth learning from humans. A human participant study was conducted where the participants were presented with various wrinkle types and tasked with flattening…

Computer Vision and Pattern Recognition · Computer Science 2024-09-09 Nilay Kant , Ashrut Aryal , Rajiv Ranganathan , Ranjan Mukherjee , Charles Owen

Real-world face detection and alignment demand an advanced discriminative model to address challenges by pose, lighting and expression. Illuminated by the deep learning algorithm, some convolutional neural networks based face detection and…

Computer Vision and Pattern Recognition · Computer Science 2017-08-01 Weilin Cong , Sanyuan Zhao , Hui Tian , Jianbing Shen

Previous face forgery detection methods mainly focus on appearance features, which may be easily attacked by sophisticated manipulation. Considering the majority of current face manipulation methods generate fake faces based on a single…

Computer Vision and Pattern Recognition · Computer Science 2024-03-11 Jingyi Zhang , Peng Zhang , Jingjing Wang , Di Xie , Shiliang Pu

This paper presents FSNet, a deep generative model for image-based face swapping. Traditionally, face-swapping methods are based on three-dimensional morphable models (3DMMs), and facial textures are replaced between the estimated…

Computer Vision and Pattern Recognition · Computer Science 2022-07-04 Ryota Natsume , Tatsuya Yatagawa , Shigeo Morishima

It plays a fundamental role to compactly represent the visual information towards the optimization of the ultimate utility in myriad visual data centered applications. With numerous approaches proposed to efficiently compress the texture…

Computer Vision and Pattern Recognition · Computer Science 2021-04-20 Shurun Wang , Shiqi Wang , Wenhan Yang , Xinfeng Zhang , Shanshe Wang , Siwei Ma , Wen Gao

While existing methods for 3D face reconstruction from in-the-wild images excel at recovering the overall face shape, they commonly miss subtle, extreme, asymmetric, or rarely observed expressions. We improve upon these methods with SMIRK…

Computer Vision and Pattern Recognition · Computer Science 2025-03-14 George Retsinas , Panagiotis P. Filntisis , Radek Danecek , Victoria F. Abrevaya , Anastasios Roussos , Timo Bolkart , Petros Maragos

Probabilistic Face Embeddings (PFE) can improve face recognition performance in unconstrained scenarios by integrating data uncertainty into the feature representation. However, existing PFE methods tend to be over-confident in estimating…

Computer Vision and Pattern Recognition · Computer Science 2021-06-23 Kai Chen , Qi Lv , Taihe Yi

Face manipulation has shown remarkable advances with the flourish of Generative Adversarial Networks. However, due to the difficulties of controlling structures and textures, it is challenging to model poses and expressions simultaneously,…

Computer Vision and Pattern Recognition · Computer Science 2021-01-19 Chaoyou Fu , Yibo Hu , Xiang Wu , Guoli Wang , Qian Zhang , Ran He

Efficient data compression is crucial for the storage and transmission of visual data. However, in facial expression recognition (FER) tasks, lossy compression often leads to feature degradation and reduced accuracy. To address these…

Computer Vision and Pattern Recognition · Computer Science 2025-09-23 Xiumei Li , Marc Windsheimer , Misha Sadeghi , Björn Eskofier , André Kaup

Finding a suitable density function is essential for density-based clustering algorithms such as DBSCAN and DPC. A naive density corresponding to the indicator function of a unit $d$-dimensional Euclidean ball is commonly used in these…

Machine Learning · Computer Science 2021-10-15 Chao Zheng , Yingjie Chen , Chong Chen , Jianqiang Huang , Xian-Sheng Hua

Daily monitoring of intra-personal facial changes associated with health and emotional conditions has great potential to be useful for medical, healthcare, and emotion recognition fields. However, the approach for capturing intra-personal…

Computer Vision and Pattern Recognition · Computer Science 2025-04-29 Yusuke Akamatsu , Terumi Umematsu , Hitoshi Imaoka , Shizuko Gomi , Hideo Tsurushima

We present a method for fine-grained face manipulation. Given a face image with an arbitrary expression, our method can synthesize another arbitrary expression by the same person. This is achieved by first fitting a 3D face model and then…

Computer Vision and Pattern Recognition · Computer Science 2019-02-26 Zhenglin Geng , Chen Cao , Sergey Tulyakov

Accurate facial expression imitation on human-face robots is crucial for achieving natural human-robot interaction. Most existing methods have achieved photorealistic expression imitation through mapping 2D facial landmarks to a robot's…

Robotics · Computer Science 2026-03-10 Xu Chen , Rui Gao , Che Sun , Zhehang Liu , Yuwei Wu , Shuo Yang , Yunde Jia

Example-based mesh deformation methods are powerful tools for realistic shape editing. However, existing techniques typically combine all the example deformation modes, which can lead to overfitting, i.e. using a overly complicated model to…

Graphics · Computer Science 2017-09-06 Lin Gao , Yu-Kun Lai , Jie Yang , Ling-Xiao Zhang , Leif Kobbelt , Shihong Xia

A face model is a mathematical representation of the distinct features of a human face. Traditionally, face models were built using a set of fiducial points or landmarks, each point ideally located on a facial feature, i.e., corner of the…

Computer Vision and Pattern Recognition · Computer Science 2023-11-07 Jagmohan Meher , Hector Allende-Cid , Torbjörn E. M. Nordling