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Related papers: Laplace Landmark Localization

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Accurate face landmark localization is an essential part of face recognition, reconstruction and morphing. To accurately localize face landmarks, we present our heatmap regression approach. Each model consists of a MobileNetV2 backbone…

Computer Vision and Pattern Recognition · Computer Science 2021-03-09 Samuel W. F. Earp , Aubin Samacoits , Sanjana Jain , Pavit Noinongyao , Siwa Boonpunmongkol

Facial landmark detection is an important task in computer vision with numerous applications, such as head pose estimation, expression analysis, face swapping, etc. Heatmap regression-based methods have been widely used to achieve…

Computer Vision and Pattern Recognition · Computer Science 2025-08-22 Chiao-An Yang , Raymond A. Yeh

In this work we focus on learning facial representations that can be adapted to train effective face recognition models, particularly in the absence of labels. Firstly, compared with existing labelled face datasets, a vastly larger…

Computer Vision and Pattern Recognition · Computer Science 2024-03-14 Zhonglin Sun , Chen Feng , Ioannis Patras , Georgios Tzimiropoulos

We present two techniques to improve landmark localization in images from partially annotated datasets. Our primary goal is to leverage the common situation where precise landmark locations are only provided for a small data subset, but…

Computer Vision and Pattern Recognition · Computer Science 2018-10-30 Sina Honari , Pavlo Molchanov , Stephen Tyree , Pascal Vincent , Christopher Pal , Jan Kautz

Dense facial landmark detection is one of the key elements of face processing pipeline. It is used in virtual face reenactment, emotion recognition, driver status tracking, etc. Early approaches were suitable for facial landmark detection…

Computer Vision and Pattern Recognition · Computer Science 2022-04-26 Kostiantyn Khabarlak , Larysa Koriashkina

Localization of salient facial landmark points, such as eye corners or the tip of the nose, is still considered a challenging computer vision problem despite recent efforts. This is especially evident in unconstrained environments, i.e., in…

Computer Vision and Pattern Recognition · Computer Science 2015-01-21 Nenad Markuš , Miroslav Frljak , Igor S. Pandžić , Jörgen Ahlberg , Robert Forchheimer

Landmark detection algorithms trained on high resolution images perform poorly on datasets containing low resolution images. This deters the performance of algorithms relying on quality landmarks, for example, face recognition. To the best…

Computer Vision and Pattern Recognition · Computer Science 2019-08-01 Amit Kumar , Rama Chellappa

We address the problem of visual place recognition with perceptual changes. The fundamental problem of visual place recognition is generating robust image representations which are not only insensitive to environmental changes but also…

Computer Vision and Pattern Recognition · Computer Science 2019-04-16 Zhe Xin , Yinghao Cai , Tao Lu , Xiaoxia Xing , Shaojun Cai , Jixiang Zhang , Yiping Yang , Yanqing Wang

Modern face alignment methods have become quite accurate at predicting the locations of facial landmarks, but they do not typically estimate the uncertainty of their predicted locations nor predict whether landmarks are visible. In this…

Computer Vision and Pattern Recognition · Computer Science 2020-04-08 Abhinav Kumar , Tim K. Marks , Wenxuan Mou , Ye Wang , Michael Jones , Anoop Cherian , Toshiaki Koike-Akino , Xiaoming Liu , Chen Feng

In this paper, we address the problem of landmark-based visual place recognition. In the state-of-the-art method, accurate object proposal algorithms are first leveraged for generating a set of local regions containing particular landmarks…

Robotics · Computer Science 2018-08-24 Bo Yang , Jun Li , Xiaosu Xu , Hong Zhang

We propose a general purpose approach to detect landmarks with improved temporal consistency, and personalization. Most sparse landmark detection methods rely on laborious, manually labelled landmarks, where inconsistency in annotations…

Computer Vision and Pattern Recognition · Computer Science 2021-04-12 David Ferman , Gaurav Bharaj

Deep Learning models based on heatmap regression have revolutionized the task of facial landmark localization with existing models working robustly under large poses, non-uniform illumination and shadows, occlusions and self-occlusions, low…

Computer Vision and Pattern Recognition · Computer Science 2021-11-04 Adrian Bulat , Enrique Sanchez , Georgios Tzimiropoulos

Facial landmark localization is a very crucial step in numerous face related applications, such as face recognition, facial pose estimation, face image synthesis, etc. However, previous competitions on facial landmark localization (i.e.,…

Computer Vision and Pattern Recognition · Computer Science 2019-07-25 Yinglu Liu , Hao Shen , Yue Si , Xiaobo Wang , Xiangyu Zhu , Hailin Shi , Zhibin Hong , Hanqi Guo , Ziyuan Guo , Yanqin Chen , Bi Li , Teng Xi , Jun Yu , Haonian Xie , Guochen Xie , Mengyan Li , Qing Lu , Zengfu Wang , Shenqi Lai , Zhenhua Chai , Xiaoming Wei

We present a novel boundary-aware face alignment algorithm by utilising boundary lines as the geometric structure of a human face to help facial landmark localisation. Unlike the conventional heatmap based method and regression based…

Computer Vision and Pattern Recognition · Computer Science 2018-05-29 Wayne Wu , Chen Qian , Shuo Yang , Quan Wang , Yici Cai , Qiang Zhou

Existing deep learning based facial landmark detection methods have achieved excellent performance. These methods, however, do not explicitly embed the structural dependencies among landmark points. They hence cannot preserve the geometric…

Computer Vision and Pattern Recognition · Computer Science 2022-06-29 Lisha Chen , Hui Su , Qiang Ji

Landmark localization is a challenging problem in computer vision with a multitude of applications. Recent deep learning based methods have shown improved results by regressing likelihood maps instead of regressing the coordinates directly.…

Computer Vision and Pattern Recognition · Computer Science 2019-08-06 Brian Teixeira , Birgi Tamersoy , Vivek Singh , Ankur Kapoor

Face image super-resolution aims to recover high-resolution facial images from severely degraded inputs. Under extreme upscaling factors, fine facial details are often lost, making accurate reconstruction challenging. Existing methods…

Computer Vision and Pattern Recognition · Computer Science 2026-05-15 Riccardo Carraro , Anna Briotto , Endi Hysa , Marco Fiorucci , Lamberto Ballan

Watermarking is a tool for actively identifying and attributing the images generated by latent diffusion models. Existing methods face the dilemma of image quality and watermark robustness. Watermarks with superior image quality usually…

Computer Vision and Pattern Recognition · Computer Science 2024-09-27 Zheling Meng , Bo Peng , Jing Dong

Facial landmark detection has been studied over decades. Numerous neural network (NN)-based approaches have been proposed for detecting landmarks, especially the convolutional neural network (CNN)-based approaches. In general, CNN-based…

Computer Vision and Pattern Recognition · Computer Science 2020-05-19 Chih-Fan Hsu , Chia-Ching Lin , Ting-Yang Hung , Chin-Laung Lei , Kuan-Ta Chen

This paper addresses the challenge of localization of anatomical landmarks in knee X-ray images at different stages of osteoarthritis (OA). Landmark localization can be viewed as regression problem, where the landmark position is directly…

Computer Vision and Pattern Recognition · Computer Science 2019-09-10 Aleksei Tiulpin , Iaroslav Melekhov , Simo Saarakkala
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