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English(EN) The Target Is a Predicate: Predicate-State Grounding for Semantic-Level Video Reasoning Segmentation

新的PS-VRS方法通过动态谓词改进视频推理分割

研究人员推出谓词状态视频推理分割(PS-VRS),一种新的视频分析方法,侧重于动态谓词而非固定的对象身份。该方法旨在通过显式建模谓词随时间的激活和空置状态来提高分割的准确性。为了支持这一点,他们创建了PS-Bench,一个包含2000多个视频的基准数据集,并对谓词状态和掩码进行了详细注释。他们提出的谓词状态接地(PSG)管道,它预测状态令牌,将它们与视频帧对齐,并且仅为激活状态发出掩码,与现有方法相比显示出显著的改进。 AI

影响 这项研究可能带来更复杂的视频分析工具,能够理解动态的视觉关系和事件。

排序理由 该集群描述了一篇介绍视频推理分割新方法和基准的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CV 阅读 →

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新的PS-VRS方法通过动态谓词改进视频推理分割

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该集群描述了一篇介绍视频推理分割新方法和基准的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.CV TIER_1 English(EN) · Yuhuan Hong, Yiming Ren, Zhiqiang Lin, Feize Wu, Xingyun Liu, Yitong Xie, Lei Zhou, Lisheng Wu, Junjie Wang, Yujiu Yang ·

    目标是谓词:用于语义级视频推理分割的谓词状态接地

    arXiv:2611.13785v1 Announce Type: new Abstract: In this paper, we introduce Predicate-State Video Reasoning Segmentation (PS-VRS), where a query defines a dynamic predicate $P(o,t)$ over objects and time rather than a fixed object identity. Existing methods typically treat the ta…