论文概要
研究领域: CV 作者: Boyang Wang, Guangyi Xu, Zhipeng Tang 发布时间: 2025-04-29 arXiv: 2504.20683
中文摘要
OmniShotCut 将镜头边界检测(SBD)形式化为结构化关系预测，通过基于镜头查询的密集视频Transformer联合估计镜头范围内的内部镜头关系和镜头间的跨镜头关系。为避免不精确的手动标注，采用完全合成的过渡合成流程自动生成主要过渡族。同时引入 OmniShotCutBench 现代宽域基准实现整体和诊断性评估。
原文摘要
Shot Boundary Detection (SBD) aims to automatically identify shot changes and divide a video into coherent shots. While SBD was widely studied in the literature, existing state-of-the-art methods often produce non-interpretable boundaries on transitions, miss subtle yet harmful discontinuities, and rely on noisy, low-diversity annotations and outdated benchmarks. To alleviate these limitations, we propose OmniShotCut to formulate SBD as structured relational prediction, jointly estimating shot ranges with intra-shot relations and inter-shot relations, by a shot query-based dense video Transformer. To avoid imprecise manual labeling, we adopt a fully synthetic transition synthesis pipeline that automatically reproduces major transition families with precise boundaries and parameterized vari...
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