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Makeup is widely used to improve facial attractiveness and is well accepted by the public. However, different makeup styles will result in significant facial appearance changes. It remains a challenging problem to match makeup and…

Computer Vision and Pattern Recognition · Computer Science 2017-11-23 Yi Li , Lingxiao Song , Xiang Wu , Ran He , Tieniu Tan

Makeup transfer is not only to extract the makeup style of the reference image, but also to render the makeup style to the semantic corresponding position of the target image. However, most existing methods focus on the former and ignore…

Computer Vision and Pattern Recognition · Computer Science 2021-12-08 Zhaoyang Sun , Yaxiong Chen , Shengwu Xiong

Neural radiance fields (NeRF) based methods have shown amazing performance in synthesizing 3D-consistent photographic images, but fail to generate multi-view portrait drawings. The key is that the basic assumption of these methods -- a…

Computer Vision and Pattern Recognition · Computer Science 2023-05-05 Biao Ma , Fei Gao , Chang Jiang , Nannan Wang , Gang Xu

In recent years, deep learning has greatly streamlined the process of manipulating photographic face images. Aware of the potential dangers, researchers have developed various tools to spot these counterfeits. Yet, none asks the fundamental…

Computer Vision and Pattern Recognition · Computer Science 2025-04-08 Mian Zou , Baosheng Yu , Yibing Zhan , Siwei Lyu , Kede Ma

Facial analysis models are increasingly used in applications that have serious impacts on people's lives, ranging from authentication to surveillance tracking. It is therefore critical to develop techniques that can reveal unintended biases…

Computer Vision and Pattern Recognition · Computer Science 2024-03-14 Remi Denton , Ben Hutchinson , Margaret Mitchell , Timnit Gebru , Andrew Zaldivar

AIGC-based image editing technology has greatly simplified the realistic-level image modification, causing serious potential risks of image forgery. This paper introduces a new approach to tampering detection using the Segment Anything…

Computer Vision and Pattern Recognition · Computer Science 2025-12-01 Qi Song , Ziyuan Luo , Renjie Wan

In recent years, image generation has made great strides in improving the quality of images, producing high-fidelity ones. Also, quite recently, there are architecture designs, which enable GAN to unsupervisedly learn the semantic…

Computer Vision and Pattern Recognition · Computer Science 2022-08-10 Xin Jin , Shu Zhao , Le Zhang , Xin Zhao , Qiang Deng , Chaoen Xiao

Recent advances in image generation gave rise to powerful tools for semantic image editing. However, existing approaches can either operate on a single image or require an abundance of additional information. They are not capable of…

Computer Vision and Pattern Recognition · Computer Science 2020-10-09 Evangelos Ntavelis , Andrés Romero , Iason Kastanis , Luc Van Gool , Radu Timofte

Deepfake detection refers to detecting artificially generated or edited faces in images or videos, which plays an essential role in visual information security. Despite promising progress in recent years, Deepfake detection remains a…

Computer Vision and Pattern Recognition · Computer Science 2023-12-11 Chunlei Peng , Huiqing Guo , Decheng Liu , Nannan Wang , Ruimin Hu , Xinbo Gao

Facial makeup editing aims to realistically transfer makeup from a reference to a target face. Existing methods often produce low-quality results with coarse makeup details and struggle to preserve both identity and makeup fidelity, mainly…

Computer Vision and Pattern Recognition · Computer Science 2025-08-11 Huadong Wu , Yi Fu , Yunhao Li , Yuan Gao , Kang Du

Facial Image inpainting aim is to restore the missing or corrupted regions in face images while preserving identity, structural consistency and photorealistic image quality, a task specifically created for photo restoration. Though there…

Computer Vision and Pattern Recognition · Computer Science 2026-02-17 Abhigyan Bhattacharya , Hiranmoy Roy , Debotosh Bhattacharjee

Although significant progress has been made in synthesizing high-quality and visually realistic face images by unconditional Generative Adversarial Networks (GANs), there still lacks of control over the generation process in order to…

Computer Vision and Pattern Recognition · Computer Science 2020-12-23 Xianxu Hou , Xiaokang Zhang , Linlin Shen , Zhihui Lai , Jun Wan

Recently, we have seen an increase in the global facial recognition market size. Despite significant advances in face recognition technology with the adoption of convolutional neural networks, there are still open challenges, such as when…

Computer Vision and Pattern Recognition · Computer Science 2021-10-19 Marcus de Assis Angeloni , Helio Pedrini

Facial stylization aims to transform facial images into appealing, high-quality stylized portraits, with the critical challenge of accurately learning the target style while maintaining content consistency with the original image. Although…

Computer Vision and Pattern Recognition · Computer Science 2025-07-01 Zhanyi Lu , Yue Zhou

The rapid advancement in deep learning makes the differentiation of authentic and manipulated facial images and video clips unprecedentedly harder. The underlying technology of manipulating facial appearances through deep generative…

Computer Vision and Pattern Recognition · Computer Science 2021-09-08 Sm Zobaed , Md Fazle Rabby , Md Istiaq Hossain , Ekram Hossain , Sazib Hasan , Asif Karim , Khan Md. Hasib

Modern AI tools, such as generative adversarial networks, have transformed our ability to create and modify visual data with photorealistic results. However, one of the deleterious side-effects of these advances is the emergence of…

Computer Vision and Pattern Recognition · Computer Science 2021-10-25 Mingyang Xie , Manav Kulshrestha , Shaojie Wang , Jinghan Yang , Ayan Chakrabarti , Ning Zhang , Yevgeniy Vorobeychik

Improper exposure often leads to severe loss of details, color distortion, and reduced contrast. Exposure correction still faces two critical challenges: (1) the ignorance of object-wise regional semantic information causes the color shift…

Computer Vision and Pattern Recognition · Computer Science 2026-01-29 Puzhen Wu , Han Weng , Quan Zheng , Yi Zhan , Hewei Wang , Yiming Li , Jiahui Han , Rui Xu

Accurate age verification can protect underage users from unauthorized access to online platforms and e-commerce sites that provide age-restricted services. However, accurate age estimation can be confounded by several factors, including…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Ekta Gavas , Sudipta Banerjee , Chinmay Hegde , Nasir Memon

Current AI-assisted skin image diagnosis has achieved dermatologist-level performance in classifying skin cancer, driven by rapid advancements in deep learning architectures. However, unlike traditional vision tasks, skin images in general…

Computer Vision and Pattern Recognition · Computer Science 2025-01-17 Xin Hu , Janet Wang , Jihun Hamm , Rie R Yotsu , Zhengming Ding

Medical image segmentation, or computing voxelwise semantic masks, is a fundamental yet challenging task to compute a voxel-level semantic mask. To increase the ability of encoder-decoder neural networks to perform this task across large…

Computer Vision and Pattern Recognition · Computer Science 2021-11-10 Ho Hin Lee , Yucheng Tang , Qi Yang , Xin Yu , Shunxing Bao , Leon Y. Cai , Lucas W. Remedios , Bennett A. Landman , Yuankai Huo
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