arXiv:2606. 28570v1 Announce Type: cross Abstract: Athlete assessment is a critical process for tracking physical progress and identifying elite talent.
By Deep Ghosal, Ishani Sen, Wazib Ansar, Amlan Chakrabarti
arXiv:2602. 12080v2 Announce Type: replace Abstract: Despite recent advances in AI, event data collection in soccer still relies heavily on labor-intensive manual annotation.
By Hyunsung Kim, Kunhee Lee, Sangwoo Seo, Sang-Ki Ko, Jinsung Yoon, Chanyoung Park
arXiv:2608. 19723v1 Announce Type: cross Abstract: Streaming video understanding requires models to causally update state as video arrives and organize growing history into semantic units that can evolve, persist, and be recalled under bounded computation and memory.
By Chenxi Shao, Bozhong Wang, Jiaxin Huang, Zhao Liu, Sunwei Zhu, Tianxin Hang, Gaoqi He, Yang Li, Changbo Wang
arXiv:2609.39300v1 Announce Type: new
Abstract: Recent advances in computer vision have made broadcast sports videos increasingly useful for event analysis, performance assessment, and player-safety...
By Ahmed Endris Hasen, Muhammad Shahzad Khan, Nikolaos Passalis, Jenni Raitoharju
arXiv:2608. 20087v1 Announce Type: cross Abstract: Humanoid robots have recently demonstrated promising capabilities in real-world ball sports.
By Tao Huang, Ruofei Liu, Xuchen Tang, Xinyin Zhang, Junli Ren, Huayi Wang, Feiyu Jia, Yukai Qi, Kangning Yin, Weishuai Zeng, Lipeng Chen, Xi Li, Ting Wu, Kailin Li, Ruoli Dai, Jingbo Wang, Lei Han, Jiangmiao Pang
The paper introduces the Semantic Action Graph, a lightweight domain schema that models a sports match using performer, action, recipient, moment, and state nodes linked by role, temporal, and outcome edges. This structure supports both an agentic pipeline for generating narrated highlights and a visual interface that lets viewers query and inspect the same representation. In a prototype called SportSAGE, 12 soccer fans reported satisfaction with the generated highlights and used the graph interface to search, navigate, and interpret match moments.
By Tica Lin, Deepak Chandran, Gauri Jagatap, Chen Chen, Andrea Fanelli, David Gunawan, Josh Kimball