Zobrazeno 1 - 10
of 21
pro vyhledávání: '"Jakub Kanis"'
Publikováno v:
Sensors, Vol 23, Iss 12, p 5509 (2023)
This work presents a novel transformer-based method for hand pose estimation—DePOTR. We test the DePOTR method on four benchmark datasets, where DePOTR outperforms other transformer-based methods while achieving results on par with other state-of-t
Externí odkaz:
https://doaj.org/article/2822cf0f247744f3880728292f26708a
Publikováno v:
IEEE Access, Vol 9, Pp 10533-10547 (2021)
In this article we tackle the problem of hand pose estimation when the hand is interacting with various objects from egocentric viewpoint. This entails a frequent occlusion of parts of the hand by the object and also self-occlusions of the hand. We u
Externí odkaz:
https://doaj.org/article/1d9bff3b0b7f40b9a76e33d812fe6174
Publikováno v:
Sensors, Vol 22, Iss 13, p 5043 (2022)
In this paper, we dive into sign language recognition, focusing on the recognition of isolated signs. The task is defined as a classification problem, where a sequence of frames (i.e., images) is recognized as one of the given sign language glosses.
Externí odkaz:
https://doaj.org/article/7b78a784ec7a4db7ab39ca6e958d2272
Publikováno v:
Sensors; Volume 23; Issue 12; Pages: 5509
This work presents a novel transformer-based method for hand pose estimation—DePOTR. We test the DePOTR method on four benchmark datasets, where DePOTR outperforms other transformer-based methods while achieving results on par with other state-of-t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=multidiscipl::4d893d3648351775e162af281c96d48c
Publikováno v:
Sensors; Volume 22; Issue 13; Pages: 5043
In this paper, we dive into sign language recognition, focusing on the recognition of isolated signs. The task is defined as a classification problem, where a sequence of frames (i.e., images) is recognized as one of the given sign language glosses.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0b9b6cbdaf9a3b2a54f527d3d9db1a12
http://hdl.handle.net/11025/51652
http://hdl.handle.net/11025/51652
Publikováno v:
CVPR Workshops
This paper presents a method for automatic sign language recognition that was utilized in the CVPR 2021 ChaLearn Challenge (RGB track). Our method is composed of several approaches combined in an ensemble scheme to perform isolated sign-gesture recog
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7313864f15e232a39ed75207c57f8c2e
https://doi.org/10.1109/cvprw53098.2021.00381
https://doi.org/10.1109/cvprw53098.2021.00381
Autor:
Jan Zelinka, Jakub Kanis
Publikováno v:
WACV
Tento článek se zabývá syntézou znakového jazyka typu text-video. Místo přímé produkce videa jsme se zaměřili na výrobu skeletových modelů. Naším hlavním cílem v tomto příspěvku bylo navrhnout plně end-to-end systém automatick
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c0d7b38f1f60c0f7bc34091ca4c215b2
https://doi.org/10.1109/wacv45572.2020.9093516
https://doi.org/10.1109/wacv45572.2020.9093516
Autor:
Shreyas Hampali, Fu Xiong, Shipeng Xie, Zdenek Krnoul, Weiguo Zhou, Sijia Mei, Seungryul Baek, Zhaohui Zhang, Haifeng Sun, Guillermo Garcia-Hernando, Yang Xiao, Dongheui Lee, Angela Yao, Umar Iqbal, Mahdi Rad, Marek Hrúz, Adrian Spurr, Qingfu Wan, Zhiguo Cao, Junsong Yuan, Vincent Lepetit, Pavlo Molchanov, Romain Brégier, Pengfei Ren, Yunhui Liu, Shile Li, Philippe Weinzaepfel, Linlin Yang, Anil Armagan, Weiting Huang, Grégory Rogez, Boshen Zhang, Tae-Kyun Kim, Mingxiu Chen, Jakub Kanis
Publikováno v:
Computer Vision – ECCV 2020 ISBN: 9783030585914
ECCV (23)
ECCV (23)
We study how well different types of approaches generalise in the task of 3D hand pose estimation under single hand scenarios and hand-object interaction. We show that the accuracy of state-of-the-art methods can drop, and that they fail mostly on po
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::334571a0b2fa3856d677209cb23e6322
Publikováno v:
Speech and Computer ISBN: 9783030260606
SPECOM
SPECOM
Tento článek se zabývá odhadem pozice rukou z jediného hloubkového obrazu. Představujeme metodu, která je založena na popisu pozice ruky prostřednictvím lokálních rotací kostí, které byly trénovány diskriminačně end-to-end módem
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::00f29cdf241129cf1b01ad0bfe2a305d
https://doi.org/10.1007/978-3-030-26061-3_22
https://doi.org/10.1007/978-3-030-26061-3_22