Zobrazeno 1 - 10
of 248
pro vyhledávání: '"Jiri Matas"'
Autor:
Tomas Vojir, Jiri Matas
Publikováno v:
2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV).
Publikováno v:
IEEE Sensors Journal. 21:23317-23324
The paper addresses acoustic vehicle speed estimation using single sensor measurements. We introduce a new speed-dependent feature based on the attenuation of the sound amplitude. The feature is predicted from the audio signal and used as input to a
Autor:
Sylvia Cremer, Elisabeth Naderlinger, Christopher D. Pull, Barbara Casillas-Pérez, Filip Naiser, Jiri Matas
Publikováno v:
Ecology Letters
Infections early in life can have enduring effects on an organism's development and immunity. In this study, we show that this equally applies to developing 'superorganisms'--incipient social insect colonies. When we exposed newly mated Lasius niger
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8764d7921bcfa1b4720ae4f508f14b32
https://doi.org/10.1111/ele.13907
https://doi.org/10.1111/ele.13907
Autor:
Philip H. S. Torr, Haitao Zhang, Bin Yan, Ziyi Cheng, Fahad Shahbaz Khan, Shoumeng Qiu, Bineng Zhong, Ondrej Drbohlav, Bo Liu, Ozgun Cirakman, Kristian Simonato, Danda Pani Paudel, Xin Chen, Xiangyuan Lan, Wei Lu, Martin Danelljan, Felix Järemo Lawin, Qing Guo, Luka Čehovin Zajc, Christoph Mayer, Xiao Ke, Wankou Yang, Yanyan Huang, Xiaoning Song, Dong Wang, Felix Juefei-Xu, Xue-Feng Zhu, Guangting Wang, Jingen Liu, Jani Käpylä, Ales Leonardis, Christian Micheloni, Paul Voigtlaender, Yu-Chen Chiu, Lijun Wang, Shengyong Chen, Linyuan Wang, Shaochuan Zhao, Ling Shao, Yong Wang, Li Liu, Xiaoyun Yang, Liangliang Wang, Rongrong Ji, Gustavo Fernandez, Bilge Gunsel, Xingping Dong, Fei Xie, Jun Yin, Zhangyong Tang, Michael Felsberg, Aravindh Rajiv, Andreas Robinson, Miao Cheng, Mohana Murali Dasari, Josef Kittler, Chang Liu, Wencheng Han, Zhongqun Zhang, Yuezhou Li, Bedirhan Uzun, Roman Pflugfelder, Jinyu Yang, Yu Ye, Goutam Bhat, Kangkai Zhang, Hui Li, Jiri Matas, Mohamed H. Abdelpakey, Zhen-Hua Feng, Hyung Jin Chang, Ming Zhen, Matteo Dunnhofer, Xianxian Li, Yingjie Jiang, Luc Van Gool, Matej Kristan, Xiang Xu, Bastian Leibe, Xinyu Zhang, Filiz Gurkan, Jun Ha Lee, Yunhong Wang, Niki Martinel, Shang-Jhih Jhang, Yin Jun, Jianhua Li, Chengwei Zhang, Cheng Jiang, Muhammad Rana, Jie Ma, Houwen Peng, Gustav Häger, Zhiyong Feng, Wanli Xue, Gangshan Wu, Joni-Kristian Kamarainen, Zhibin Zhang, Alireza Memarmoghadam, Qili Deng, Daniel K. Du, Shiming Ge, Mohamed Shehata, Zhihong Fu, Chunhui Zhang, Yuzhen Niu, Xiaojun Wu, Rama Krishna Sai Subrahmanyam Gorthi, Hasan Saribas, Yuzhang Gu, Kenan Dai, Furao Shen, Qingjie Liu, Byeong Hak Kim, Hakan Cevikalp, Llukman Cerkezi, Jianbing Shen, Chenyan Wu, Alan Lukezic, Jiawen Zhu, Ziang Ma, Xiaohan Zhang, Limin Wang, Radu Timofte, Chi-Yi Tsai, Song Yan, Jonathon Luiten, Huchuan Lu, Kaihua Zhang, Tianyang Xu, Yutao Cui, Xiaolin Zhang
The Visual Object Tracking challenge VOT2021 is the ninth annual tracker benchmarking activity organized by the VOT initiative. Results of 71 trackers are presented; many are state-of-the-art trackers published at major computer vision conferences or
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::717763c198da14f9ea29d111bbb1d71f
https://ora.ox.ac.uk/objects/uuid:d4585a6f-2205-4f68-b34a-8b6a61758cc8
https://ora.ox.ac.uk/objects/uuid:d4585a6f-2205-4f68-b34a-8b6a61758cc8
Publikováno v:
International Journal of Computer Vision. 129:2031-2033
Autor:
Yuhe Jin, Kwang Moo Yi, Pascal Fua, Eduard Trulls, Jiri Matas, Dmytro Mishkin, Anastasiia Mishchuk
Publikováno v:
International Journal of Computer Vision. 129:517-547
We introduce a comprehensive benchmark for local features and robust estimation algorithms, focusing on the downstream task -- the accuracy of the reconstructed camera pose -- as our primary metric. Our pipeline's modular structure allows easy integr
Publikováno v:
IEEE Transactions on Pattern Analysis and Machine Intelligence, 44 (11)
A new method for robust estimation, MAGSAC++, is proposed. It introduces a new model quality (scoring) function that does not make inlier-outlier decisions, and a novel marginalization procedure formulated as an M-estimation with a novel class of M-e
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e52d428b5011c6c176dff50d0dbd61a3
Publikováno v:
2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV).
This paper presents a novel neural architecture search method, called LiDNAS, for generating lightweight monocular depth estimation models. Unlike previous neural architecture search (NAS) approaches, where finding optimized networks are computationa
Autor:
Jiri Matas, Daniel Barath
We propose Graph-Cut RANSAC, GC-RANSAC in short, a new robust geometric model estimation method where the local optimization step is formulated as energy minimization with binary labeling, applying the graph-cut algorithm to select inliers. The minim
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::947bab3b9403e6c2f4552ab32d04b2fd
https://eprints.sztaki.hu/10367/
https://eprints.sztaki.hu/10367/
Autor:
Tetiana Martyniuk, Orest Kupyn, Yana Kurlyak, Igor Krashenyi, Jiri Matas, Viktoriia Sharmanska
We present DAD-3DHeads, a dense and diverse large-scale dataset, and a robust model for 3D Dense Head Alignment in the wild. It contains annotations of over 3.5K landmarks that accurately represent 3D head shape compared to the ground-truth scans. Th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::318d0a95c3d98434ca3f26e260076058