Visual understanding in sports has emerged as a hot topic in computer vision in recent years. Most existing basketball video datasets adopt single action or activity as sample, which can neither preserve the temporal continuity of game events nor support complex tasks such as action anticipation. To address this issue,...
Yunhao Zhao, Haoying Sun, Jiarui Li et al.· 0 citations
SafeLoop is introduced, a non-invasive external wrapper that adds hazard prediction and rollback-based recovery to a VLA model without changing its parameters, and achieves a stronger overall safety-success trade-off than alternative methods.
Zeyuan Lou, Tian-Ran Zhang, Xin-Quan Yue et al.· 0 citations
This work introduces NBA_Streaming, a large-scale benchmark for online fine-grained basketball commentary generation and proposes a causal two-stage framework that combines completion-first localization with ball-centric semantic grounding, enabling the system to identify complete events from observed streams and organ...
Li-Fang Wu, Yu-Yang Wu, Yangdong Gao et al.· 0 citations
This work proposes a novel zero-shot video captioning framework (WSV) consisting of two training stages, which first generates corresponding synthetic video latent representations via a pretrained text-to-video generation model, and designs a polisher capable of bridging the gap between real and synthetic video distrib...
Liangyu Fu, Jun-Bo Wang, Yu-Ke Li et al.· 0 citations
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