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The first possession-level basketball video dataset (PL-NBA), in which each sample is composed of a complete NBA offensive possession, is constructed, demonstrating that PL-NBA is a challenging benchmark for sports video understanding.
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.
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...
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...
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