Zobrazeno 1 - 10
of 309
pro vyhledávání: '"Wang, Yuan‐Fang"'
Autor:
Xia, Haotian, Yang, Zhengbang, Zou, Junbo, Tracy, Rhys, Wang, Yuqing, Lu, Chi, Lai, Christopher, He, Yanjun, Shao, Xun, Xie, Zhuoqing, Wang, Yuan-fang, Shen, Weining, Chen, Hanjie
Multimodal Large Language Models (MLLMs) are advancing the ability to reason about complex sports scenarios by integrating textual and visual information. To comprehensively evaluate their capabilities, we introduce SPORTU, a benchmark designed to as
Externí odkaz:
http://arxiv.org/abs/2410.08474
Autor:
Xia, Haotian, Yang, Zhengbang, Zhao, Yun, Wang, Yuqing, Li, Jingxi, Tracy, Rhys, Zhu, Zhuangdi, Wang, Yuan-fang, Chen, Hanjie, Shen, Weining
Recent integration of Natural Language Processing (NLP) and multimodal models has advanced the field of sports analytics. This survey presents a comprehensive review of the datasets and applications driving these innovations post-2020. We overviewed
Externí odkaz:
http://arxiv.org/abs/2406.12252
Autor:
Xia, Haotian, Yang, Zhengbang, Wang, Yuqing, Tracy, Rhys, Zhao, Yun, Huang, Dongdong, Chen, Zezhi, Zhu, Yan, Wang, Yuan-fang, Shen, Weining
A deep understanding of sports, a field rich in strategic and dynamic content, is crucial for advancing Natural Language Processing (NLP). This holds particular significance in the context of evaluating and advancing Large Language Models (LLMs), giv
Externí odkaz:
http://arxiv.org/abs/2402.15862
This paper presents PathFinder and PathFinderPlus, two novel end-to-end computer vision frameworks designed specifically for advanced setting strategy classification in volleyball matches from a single camera view. Our frameworks combine setting ball
Externí odkaz:
http://arxiv.org/abs/2309.14753
This research aims to improve the accuracy of complex volleyball predictions and provide more meaningful insights to coaches and players. We introduce a specialized graph encoding technique to add additional contact-by-contact volleyball context to a
Externí odkaz:
http://arxiv.org/abs/2308.11142
Autor:
Wang, Yuan-Fang
ITC/USA 2015 Conference Proceedings / The Fifty-First Annual International Telemetering Conference and Technical Exhibition / October 26-29, 2015 / Bally's Hotel & Convention Center, Las Vegas, NV
In this paper, we present our research on using
In this paper, we present our research on using
Externí odkaz:
http://hdl.handle.net/10150/596451
http://arizona.openrepository.com/arizona/handle/10150/596451
http://arizona.openrepository.com/arizona/handle/10150/596451
Autor:
Lee, Hua, Wang, Yuan-Fang
ITC/USA 2014 Conference Proceedings / The Fiftieth Annual International Telemetering Conference and Technical Exhibition / October 20-23, 2014 / Town and Country Resort & Convention Center, San Diego, CA
Tomographic imaging systems utilize vario
Tomographic imaging systems utilize vario
Externí odkaz:
http://hdl.handle.net/10150/577477
Autor:
Wang, Yuan-Fang
ITC/USA 2014 Conference Proceedings / The Fiftieth Annual International Telemetering Conference and Technical Exhibition / October 20-23, 2014 / Town and Country Resort & Convention Center, San Diego, CA
In this paper, we present our research on
In this paper, we present our research on
Externí odkaz:
http://hdl.handle.net/10150/577443
This research is intended to accomplish two goals: The first goal is to curate a large and information rich dataset that contains crucial and succinct summaries on the players' actions and positions and the back-and-forth travel patterns of the volle
Externí odkaz:
http://arxiv.org/abs/2209.13846
Multi-view learning is a learning problem that utilizes the various representations of an object to mine valuable knowledge and improve the performance of learning algorithm, and one of the significant directions of multi-view learning is sub-space l
Externí odkaz:
http://arxiv.org/abs/2201.02978