Zobrazeno 1 - 10
of 14
pro vyhledávání: '"Kanav Vats"'
Publikováno v:
IEEE Access, Vol 9, Pp 139403-139414 (2021)
Neural architecture search has proven to be highly effective in the design of efficient convolutional neural networks that are better suited for mobile deployment than hand-designed networks. Hypothesizing that neural architecture search holds great
Externí odkaz:
https://doaj.org/article/0e2a76edec5e4497b8a8ae2b4ec6a057
Tracking and identifying players is an important problem in computer vision based ice hockey analytics. Player tracking is a challenging problem since the motion of players in hockey is fast-paced and non-linear. There is also significant player-play
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a5da534cfe4ce8197549d86437685de4
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031200670
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b5b395bb6908453f4f0fdb7d9f04dd58
https://doi.org/10.1007/978-3-031-20068-7_3
https://doi.org/10.1007/978-3-031-20068-7_3
Publikováno v:
MMSports@MM
Identifying players in sports videos by recognizing their jersey numbers is a challenging task in computer vision. We have designed and implemented a multi-task learning network for jersey number recognition. In order to train a network to recognize
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d76ee264729843710d33e47f2f217518
https://doi.org/10.1145/3475722.3482794
https://doi.org/10.1145/3475722.3482794
Publikováno v:
CVPR Workshops
Existing multi-camera solutions for automatic score-keeping in steel-tip darts are very expensive and thus inaccessible to most players. Motivated to develop a more accessible low-cost solution, we present a new approach to keypoint detection and app
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::11b77f693e571cc054e5df4f2c9049a5
https://doi.org/10.1109/cvprw53098.2021.00512
https://doi.org/10.1109/cvprw53098.2021.00512
Publikováno v:
CVPR Workshops
Puck localization is an important problem in ice hockey video analytics useful for analyzing the game, determining play location, and assessing puck possession. The problem is challenging due to the small size of the puck, excessive motion blur due t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1f981ed3ed42b291bd1847504fb74a98
https://doi.org/10.1109/cvprw53098.2021.00514
https://doi.org/10.1109/cvprw53098.2021.00514
Publikováno v:
CVPR Workshops
In problems such as sports video analytics, it is difficult to obtain accurate frame level annotations and exact event duration because of the lengthy videos and sheer volume of video data. This issue is even more pronounced in fast-paced sports such
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c967b26a4bf0345d0618706f6b8d72c1
http://arxiv.org/abs/2004.06172
http://arxiv.org/abs/2004.06172
Publikováno v:
CVPR Workshops
The golf swing is a complex movement requiring considerable full-body coordination to execute proficiently. As such, it is the subject of frequent scrutiny and extensive biomechanical analyses. In this paper, we introduce the notion of golf swing seq
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a12f30e9c52880701595a8941db8bd0d
https://doi.org/10.1109/cvprw.2019.00311
https://doi.org/10.1109/cvprw.2019.00311
Publikováno v:
CRV
Current research on soccer action recognitiondoes not focus on player-level actions. We introduce thepose-projected action recognition hourglass network (PARHN) for performing player-level action recognition in soccer. Thisnetwork is inspired by ARHN
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::04d013a46bfa428b0b92503194658439
https://doi.org/10.1109/crv.2019.00035
https://doi.org/10.1109/crv.2019.00035
Publikováno v:
CRV
Current action recognition algorithms in ice hockey do not fully exploit the temporal cues available in video. To solve this challenge, we introduce a two-stream network utilizing player pose sequences and optical flow features for recognizing hockey
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bf155782886abecbe551d06c258a9322
https://doi.org/10.1109/crv.2019.00032
https://doi.org/10.1109/crv.2019.00032