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English(EN) Segmenting, Fast and Slow: Real-Time Open-Vocabulary Video Instance Segmentation with Dual-Path Processing

新的双流框架实现了实时视频实例分割

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了SegFS，一个新颖的双流框架，用于实时开放词汇视频实例分割。该方法采用快慢处理方法，其中基于对象的模型首先识别稀疏关键帧上的实例。然后，这些实例表示用于条件化一个轻量级网络，该网络在后续帧中高效地跟踪和分割实例。这种将语义理解与密集掩码预测分离的方法与现有的面向移动设备的模型相比，显著降低了延迟，同时在标准基准上保持了具有竞争力的准确性。 AI

影响 该框架可以实现移动设备上更高效、更准确的实时视频分析。

排序理由 该集群包含一篇详细介绍视频实例分割新框架的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CV 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

新的双流框架实现了实时视频实例分割

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该集群包含一篇详细介绍视频实例分割新框架的研究论文。[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) · Luca Barsellotti, Martin Sundermeyer, Mattia Segu, Nikita Araslanov, Muhammad Ferjad Naeem, Marcella Cornia, Yongqin Xian, Maxim Berman ·

    分割，快与慢：基于双路径处理的实时开放词汇视频实例分割

    arXiv:2607.00124v1 Announce Type: new Abstract: Object-centric models inspired by DETR have become the dominant paradigm for open-vocabulary video instance segmentation (OV-VIS). While recent efforts have reduced the computational cost of pixel decoding, textual modality fusion, …

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