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English(EN) CoVisco: Codec-Native Vision Encoder with Native Token Compression for Unified Image-Video Understanding

CoVisco 视觉编码器使用原生令牌压缩进行长视频理解

研究人员开发了 CoVisco,这是一种新颖的视觉编码器,旨在解决理解长视频的扩展限制。CoVisco 集成了编解码器原生输入和原生令牌压缩,使其能够一次性处理扩展的视觉序列,而无需形成密集的跨帧交互。该模型使用抽象令牌来维护视频级上下文,并且可以输出这些抽象令牌或抽象令牌与选定的块令牌的组合,以用于下游多模态大型语言模型 (MLLM)。在四段、64 帧的设置下进行测试时,CoVisco 使用的视觉令牌数量大大减少,性能与 OneVision-Encoder 相当或超出。 AI

影响 CoVisco 处理长视频的令牌压缩方法可以显著降低计算成本,从而实现更高效的多模态人工智能应用。

排序理由 该集群包含一篇详细介绍视觉语言理解新模型架构的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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CoVisco 视觉编码器使用原生令牌压缩进行长视频理解

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该集群包含一篇详细介绍视觉语言理解新模型架构的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Yulong Liu, Xiaotian Han, Junyuan Shang, Yuchen Ding, Zhenyu Zhang, Shuohuan Wang, Guibo Zhu, Sirui Han, Dianhai Yu ·

    CoVisco:原生代码编解码器,具有原生令牌压缩功能,用于统一的图像-视频理解

    arXiv:2609.39924v1 Announce Type: cross Abstract: Vision-language models face a fundamental scaling bottleneck: the number of visual tokens grows with both temporal duration and spatial resolution, making long-video understanding expensive for the vision encoder and the language …