Zobrazeno 1 - 10
of 39
pro vyhledávání: '"Klemen Grm"'
Publikováno v:
IEEE Transactions on Image Processing. 29:2150-2165
In this paper we address the problem of hallucinating high-resolution facial images from low-resolution inputs at high magnification factors. We approach this task with convolutional neural networks (CNNs) and propose a novel (deep) face hallucinatio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6cb2ae18574af1ea6b83b8dd2053a599
https://doi.org/10.1109/tip.2019.2945835
https://doi.org/10.1109/tip.2019.2945835
Autor:
Sanka Rasnayaka, Basilio Sierra, Ugur Demir, Arjan Kuijper, Mustafa Ekrem Erakin, Ana F. Sequeira, Fadi Boutros, Hazim Kemal Ekenel, Jie Zhang, Shizuma Kubo, Asaki Kataoka, Raghavendra Ramachandra, Joao Ribeiro Pinto, Dan Han, Pengcheng Fang, Shiguang Shan, Chao Zhang, Jaime S. Cardoso, Nuran Kasthuriarachchi, Naiara Aginako, Kiran B. Raja, Marcos Nieto, Pedro C. Neto, Kohei Ichikawa, Jan Niklas Kolf, Florian Kirchbuchner, Klemen Grm, Mingjie He, Fei Wang, Mohsen Saffari, Sachith Seneviratne, Vitomir Struc, David Montero, Naser Damer
Publikováno v:
IJCB
This paper presents a summary of the Masked Face Recognition Competitions (MFR) held within the 2021 International Joint Conference on Biometrics (IJCB 2021). The competition attracted a total of 10 participating teams with valid submissions. The aff
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ec95812e3127f5d6be4adc150325d0ea
https://doi.org/10.1109/ijcb52358.2021.9484337
https://doi.org/10.1109/ijcb52358.2021.9484337
Publikováno v:
EUSIPCO
Due to advances in deep learning and convolutional neural networks (CNNs) there has been significant progress in the field of visual age estimation from face images over recent years. While today’s models are able to achieve considerable age estima
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1cd9f8fc27611a62c91f1579db3aa676
https://doi.org/10.23919/eusipco47968.2020.9287219
https://doi.org/10.23919/eusipco47968.2020.9287219
Autor:
Julian Fierrez, Ruben Vera-Rodriguez, Stan Z. Li, Hugo Proença, Klemen Grm, Hazim Kemal Ekenel, Joel Brogan, Zhen Lei, Andrzej Pacut, Shengcai Liao, Vitomir Struc, Luigi De Maio, Ester Gonzalez-Sosa, Weronika Gutfeter, Javier Ortega-Garcia, Hailin Shi, Hua Gao, Mark S. Nixon, Michele Nappi, Xiangyu Zhu, Walter J. Scheirer, Daniel Riccio, Gokhan Ozbulak, Esam Ghaleb
Publikováno v:
IEEE Intelligent Systems. 33:41-67
Performing covert biometric recognition in surveillance environments has been regarded as a grand challenge, considering the adversity of the conditions where recognition should be carried out (e.g., poor resolution, bad lighting, off-pose and partia
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::eeb0e1a55fba6debecbc9de881a23022
https://doi.org/10.1109/mis.2018.033001416
https://doi.org/10.1109/mis.2018.033001416
Publikováno v:
Handbook of Vascular Biometrics ISBN: 9783030277307
In this chapter, we address the problem of biometric identity recognition from the vasculature of the human sclera. Specifically, we focus on the challenging task of multi-view sclera recognition, where the visible part of the sclera vasculature chan
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::243ac52aa4654dcba1d0d0cc5466075c
https://doi.org/10.1007/978-3-030-27731-4_13
https://doi.org/10.1007/978-3-030-27731-4_13
Publikováno v:
IWOBI
It has been a longstanding goal in computer vision to describe the 3D physical space in terms of parameterized volumetric models that would allow autonomous machines to understand and interact with their surroundings. Such models are typically motiva
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6dcc140c09884cb95e16c0bcc041d8cc
http://arxiv.org/abs/1904.06585
http://arxiv.org/abs/1904.06585
Publikováno v:
ROSUS 2019 - Računalniška obdelava slik in njena uporaba v Sloveniji 2019: Zbornik 14. strokovne konference.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f356409d84e82cd23f20e8c29f73bae3
https://doi.org/10.18690/978-961-286-244-2.7
https://doi.org/10.18690/978-961-286-244-2.7
Autor:
Houqiang Li, Huchuan Lu, Siwen Wang, Rafael Martin-Nieto, Efstratios Gavves, Feng Li, Manqiang Che, Erhan Gundogdu, Priya Mariam Raju, Xiaofan Zhang, Roman Pflugfelder, Yan Lu, Xinmei Tian, Martin Danelljan, Deepak Mishra, Guilherme Sousa Bastos, Honggang Zhang, Heng Fan, Mohamed H. Abdelpakey, Zhen-Hua Feng, Wang Wei, Andrej Muhič, Wengang Zhou, Deming Chen, Haojie Zhao, Sihang Wu, Richard M. Everson, Junfei Zhuang, Qin Zhou, Myunggu Kang, Abel Gonzalez-Garcia, Pablo Vicente-Moñivar, Richard Bowden, Horst Possegger, Yicai Yang, Andrea Vedaldi, Jaime Spencer Martin, Jongwon Choi, Yunhua Zhang, Yiannis Demiris, Seokeon Choi, Alireza Memarmoghadam, Wangmeng Zuo, Changzhen Xiong, Yuxuan Sun, Daijin Kim, Yuhong Li, Qing Guo, Tang Ming, Arnold W. M. Smeulders, Hamed Kiani Galoogahi, Zhihui Wang, Asanka G. Perera, Fahad Shahbaz Khan, George De Ath, Shuangping Huang, Qian Ruihe, Philip H. S. Torr, Haojie Li, Zhiqun He, João F. Henriques, Namhoon Lee, Chong Sun, Jorge Rodríguez Herranz, Vincenzo Santopietro, Lijun Wang, Qiang Wang, Gustavo Fernandez, Shuai Bai, Weiming Hu, Ondrej Miksik, Dongyoon Wee, Xiaohe Wu, Goutam Bhat, Yifan Jiao, A. Aydin Alatan, Alfredo Petrosino, Ran Tao, Tianyang Xu, Sergio Vivas, Cheng Tian, Yee Wei Law, Wei Feng, José M. Martínez, Luca Bertinetto, Runling Wang, Liu Si, Tianzhu Zhang, Tomas Vojir, Mario Edoardo Maresca, Lichao Zhang, Changick Kim, Luka Čehovin Zajc, Lingxiao Yang, Yan Li, Javaan Chahl, Simon Hadfield, Chong Luo, Jiří Matas, Ales Leonardis, Jack Valmadre, Pedro Senna, Josef Kittler, Klemen Grm, Cong Hao, Haibin Ling, Isabela Drummond, Zheng Zhang, Fan Yang, Joakim Johnander, Tobias Fischer, Gorthi R. K. Sai Subrahmanyam, Jinyoung Sung, Jin-Young Choi, Bo Li, Hui Zhi, Álvaro Iglesias-Arias, Joost van de Weijer, Hyung Jin Chang, Jinqing Qi, Michael Felsberg, Francesco Battistone, Sangdoo Yun, Wei Zou, Huiyun Li, Boyu Chen, Zheng Zhu, Jing Li, Abdelrahman Eldesokey, Litu Rout, Matej Kristan, Mohamed Shehata, Fei Zhao, Changsheng Xu, Alan Lukežič, Yi Wu, Wenjun Zeng, Lutao Chu, Vitomir Struc, Stuart Golodetz, Alvaro Garcia-Martin, Dong Wang, Junyu Gao, Hankyeol Lee, Hyemin Lee, Ning Wang, Wei Wu, Anfeng He, Xiaojun Wu, Rama Krishna Sai Subrahmanyam Gorthi, Payman Moallem, Peixia Li, Jinqiao Wang, Erik Velasco-Salido, Ming-Hsuan Yang
Publikováno v:
European Conference on Computer Vision
Lecture Notes in Computer Science ISBN: 9783030110086
ECCV Workshops (1)
Lecture Notes in Computer Science ISBN: 9783030110086
ECCV Workshops (1)
The Visual Object Tracking challenge VOT2018 is the sixth annual tracker benchmarking activity organized by the VOT initiative. Results of over eighty trackers are presented; many are state-of-the-art trackers published at major computer vision confe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a449874fbb7a60c1bc50564cd356140f
http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-161343
http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-161343
Publikováno v:
CVPR Workshops
Contemporary face hallucination (FH) models exhibit considerable ability to reconstruct high-resolution (HR) details from low-resolution (LR) face images. This ability is commonly learned from examples of corresponding HR-LR image pairs, created by a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f7c7a03272d0b7a236a7da8ee7383298
http://arxiv.org/abs/1812.09010
http://arxiv.org/abs/1812.09010
Deep convolutional neural networks (CNNs) based approaches are the state-of-the-art in various computer vision tasks, including face recognition. Considerable research effort is currently being directed towards further improving deep CNNs by focusing
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fdfd3356bddd4b2a41a6fd8efe4cb53c