Zobrazeno 1 - 10
of 16
pro vyhledávání: '"Luca Bertinetto"'
Training state-of-the-art vision models has become prohibitively expensive for researchers and practitioners. For the sake of accessibility and resource reuse, it is important to focus on adapting these models to a variety of downstream scenarios. An
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::efc8ab6f30b3446720cccee9d161e3d7
Publikováno v:
2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e7fdc6c92005e095922448b8ce8489ea
https://doi.org/10.1109/wacv51458.2022.00266
https://doi.org/10.1109/wacv51458.2022.00266
Publikováno v:
CVPR
Deep neural networks have improved image classification dramatically over the past decade, but have done so by focusing on performance measures that treat all classes other than the ground truth as equally wrong. This has led to a situation in which
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3725a23ea046e693d62906200e26749a
https://doi.org/10.1109/cvpr42600.2020.01252
https://doi.org/10.1109/cvpr42600.2020.01252
Autor:
Shohreh Kasaei, Shaochuan Zhao, Zhen-Hua Feng, Shuhao Chen, Xiaojun Wu, Rama Krishna Sai Subrahmanyam Gorthi, Jianlong Fu, Gustavo Fernandez, Wei Lu, Roman Pflugfelder, Haibin Ling, Yuzhang Gu, Kenan Dai, Hui Li, Martin Danelljan, Felix Järemo Lawin, Jiaqian Yu, Xiaoyun Yang, Yingming Wang, Jinyu Yang, Yuncon Yao, Gian Luca Foresti, Bedirhan Uzun, Xue-Feng Zhu, Heng Fan, Haoran Bai, Houqiang Li, Alexander G. Hauptmann, Thomas B. Schön, Guangqi Chen, Mohana Murali Dasari, Ziang Ma, Pengyu Zhang, Joni-Kristian Kamarainen, Dong Wang, Yunsung Lee, Fei Wang, Fredrik K. Gustafsson, Bin Yan, Ondrej Drbohlav, Song Yan, Fei Xie, Linyuan Wang, Michael Felsberg, Alan Lukežič, Christian Micheloni, Wengang Zhou, Yingjie Jiang, Kaicheng Yu, Chen Qian, Yu Ye, Haojie Zhao, Seyed Mojtaba Marvasti-Zadeh, Huchuan Lu, Bing Li, Jingtao Xu, Jesús Bescós, Matej Kristan, Tianyang Xu, Yushan Zhang, Hasan Saribas, Linbo He, Xiaolin Zhang, Kaiwen Liu, Jun Yin, Lijun Wang, Hakan Cevikalp, Alireza Memarmoghadam, Seokeon Choi, Alvaro Garcia-Martin, Awet Haileslassie Gebrehiwot, Zezhou Wang, Junhyun Lee, Ning Wang, Luca Bertinetto, Hari Chandana Kuchibhotla, Javad Khaghani, Anton Varfolomieiev, Luc Van Gool, Jiří Matas, Josef Kittler, Kang Yang, Xi Qiu, Philip H. S. Torr, Haitao Zhang, Xiao Ke, Ales Leonardis, Weiming Hu, Radu Timofte, Chi-Yi Tsai, Shoumeng Qiu, Zhipeng Zhang, Hossein Ghanei-Yakhdan, Houwen Peng, Luka Čehovin Zajc, Qiang Wang, Andreas Robinson, Matteo Dunnhofer, Yiwei Chen, Zhirong Wu, Jianhua Li, Miao Cheng, Yuezhou Li, Goutam Bhat, Zhijun Mai, Zhangyong Tang, Li Zhang, Li Cheng
Publikováno v:
Computer Vision – ECCV 2020 Workshops ISBN: 9783030682378
ECCV Workshops (5)
ECCV Workshops (5)
The Visual Object Tracking challenge VOT2020 is the eighth annual tracker benchmarking activity organized by the VOT initiative. Results of 58 trackers are presented; many are state-of-the-art trackers published at major computer vision conferences o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::722c41ae8bc63845cb1731bcc91fd851
http://hdl.handle.net/11390/1205562
http://hdl.handle.net/11390/1205562
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:
3DV
Many applications require a camera to be relocalised online, without expensive offline training on the target scene. Whilst both keyframe and sparse keypoint matching methods can be used online, the former often fail away from the training trajectory
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::02e5c47c8127ca12cdc7a0c0afaf7c40
Publikováno v:
ICCV
Unsupervised video object segmentation has often been tackled by methods based on recurrent neural networks and optical flow. Despite their complexity, these kinds of approaches tend to favour short-term temporal dependencies and are thus prone to ac
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::17e05c5cf6b4ce0d70ecdcf6da542776
Publikováno v:
CVPR
In this paper we illustrate how to perform both visual object tracking and semi-supervised video object segmentation, in real-time, with a single simple approach. Our method, dubbed SiamMask, improves the offline training procedure of popular fully-c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f2f1378a12f47b51364426276616121a
Publikováno v:
ECCV 2016
Lecture Notes in Computer Science
Lecture Notes in Computer Science-Computer Vision – ECCV 2016 Workshops
Lecture Notes in Computer Science ISBN: 9783319488806
ECCV Workshops (2)
Lecture Notes in Computer Science
Lecture Notes in Computer Science-Computer Vision – ECCV 2016 Workshops
Lecture Notes in Computer Science ISBN: 9783319488806
ECCV Workshops (2)
The problem of arbitrary object tracking has traditionally been tackled by learning a model of the object's appearance exclusively online, using as sole training data the video itself. Despite the success of these methods, their online-only approach
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::269c67252045eff6eeebae257de07f72
https://doi.org/10.1007/978-3-319-48881-3_56
https://doi.org/10.1007/978-3-319-48881-3_56
Autor:
Ruxandra Tapu, Tianzhu Zhang, Jaeil Cho, Dalong Du, Philip H. S. Torr, Kris M. Kitani, Deepak Mishra, Wenbing Tao, Fahad Shahbaz Khan, Luka Čehovin Zajc, Boyu Chen, Jae-chan Jeong, Andrea Vedaldi, Dawei Du, Jianke Zhu, Bogdan Mocanu, Weiming Hu, Alvaro Garcia-Martin, Jingyu Liu, João F. Henriques, Yang Li, Kai Chen, Junliang Xing, Luca Bertinetto, Chang Huang, Jiri Matas, Nianhao Xie, Risheng Liu, Payman Moallem, Guan Huang, Chong Sun, Qiang Wang, Roman Pflugfelder, David Zhang, Yifan Xing, Titus Zaharia, Gustavo Fernandez, Erhan Gundogdu, Karel Lebeda, Lingxiao Yang, Francesco Battistone, Guilherme Sousa Bastos, Junfei Zhuang, Matej Kristan, Zhipeng Zhang, Changsheng Xu, Vincenzo Santopietro, Matthias Mueller, Ning Wang, Ke Gao, Gustav Häger, Andrej Muhič, Pedro Senna, Richard Bowden, Wengang Zhou, Zhiqun He, Ming-Hsuan Yang, Qifeng Yu, Alireza Memarmoghadam, Jin Gao, Ondrej Miksik, Lei Zhang, Zheng Zhu, Alfredo Petrosino, Ales Leonardis, Tomas Vojir, Yingruo Fan, Siwei Lyu, Houqiang Li, Pallavi Venugopal M, Gorthi R. K. Sai Subrahmanyam, Longyin Wen, Xiao Bian, José M. Martínez, Antoine Tran, Michael Felsberg, Wei Zou, Wenbo Li, Jana Noskova, Sunglok Choi, Isabela Drummond, Xianguo Yu, Alan Lukezic, Stuart Golodetz, Abdelrahman Eldesokey, Lijun Wang, Erik Velasco-Salido, Huchuan Lu, Antoine Manzanera, Simon Hadfield, Ji-Wan Kim, Qingming Huang, Mengdan Zhang, Rafael Martin-Nieto, Goutam Bhat, Jae-Yeong Lee, Martin Danelljan, A. Aydin Alatan, Kannappan Palaniappan, Jack Valmadre, Guna Seetharaman, Junyu Gao, Hongliang Zhang, Mahdieh Poostchi
Publikováno v:
ICCV Workshops
The Visual Object Tracking challenge VOT2017 is the fifth annual tracker benchmarking activity organized by the VOT initiative. Results of 51 trackers are presented; many are state-of-the-art published at major computer vision conferences or journals
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f678b27c8d8099f3da3923b28010438b
https://doi.org/10.1109/iccvw.2017.230
https://doi.org/10.1109/iccvw.2017.230