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CoVisco vision encoder uses native token compression for long video understanding

By PulseAugur Editorial · [1 sources] ·

Researchers have developed CoVisco, a novel vision encoder designed to address the scaling limitations in understanding long videos. CoVisco integrates codec-native input with native token compression, allowing it to process extended visual sequences in a single pass without forming dense cross-frame interactions. The model uses abstract tokens to maintain video-level context and can output either these abstract tokens or a combination of abstract and selected patch tokens for downstream multimodal large language models (MLLMs). When tested with a four-segment, 64-frame setting, CoVisco achieved performance comparable to or exceeding the OneVision-Encoder using significantly fewer visual tokens. AI

IMPACT CoVisco's approach to token compression could significantly reduce the computational cost of processing long videos, enabling more efficient multimodal AI applications.

RANK_REASON The cluster contains a research paper detailing a new model architecture for vision-language understanding. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

CoVisco vision encoder uses native token compression for long video understanding

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The cluster contains a research paper detailing a new model architecture for vision-language understanding. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [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: Codec-Native Vision Encoder with Native Token Compression for Unified Image-Video Understanding

    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 …

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