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English(EN) WeVisOne-VL: Unified Visual Perception from Objects to Pixels

WeVisOne-VL 在新的视觉语言模型中统一了对象和像素感知

作者 PulseAugur 编辑部 · [2 个来源] ·

研究人员推出 WeVisOne-VL，这是一种新颖的视觉语言模型，旨在统一对象级和像素级的视觉感知。该模型通过采用结构化下一个 token 预测和专门的像素解码器，支持包括对象检测、OCR 和分割在内的广泛任务。WeVisOne-VL 在众多基准测试中表现出色，并已发布给开源社区，以促进可靠感知系统的进步。 AI

影响 该模型对对象和像素感知的统一方法可能导致更强大、更通用的 AI 系统，以应对现实世界的视觉任务。

排序理由 该集群描述了一篇新的研究论文和模型发布，详细介绍了视觉语言模型的进展。

在 Hugging Face Daily Papers 阅读 →

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WeVisOne-VL 在新的视觉语言模型中统一了对象和像素感知

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该集群描述了一篇新的研究论文和模型发布，详细介绍了视觉语言模型的进展。
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报道来源 [2]

  1. Hugging Face Daily Papers TIER_1 English(EN) ·

    WeVisOne-VL：从物体到像素的统一视觉感知

    WeVisOne-VL unifies object-level and pixel-level visual perception via structured token prediction, supporting detection, localization, counting, OCR, segmentation, and matting with a lightweight pixel decoder and multi-stage training.

  2. arXiv cs.CV TIER_1 English(EN) · Tianming Liang, Junyi Pan, Yuxi Li, Canmiao Fu, Zhipeng Huang, Chong Sun, Chen Li, Jing Lyu ·

    WeVisOne-VL：从物体到像素的统一视觉感知

    arXiv:2610.31329v1 Announce Type: new Abstract: Existing vision-language models (VLMs) remain unreliable for fine-grained visual perception. In this report, we present WeVisOne-VL (WeChat Vision All-in-One), a powerful VLM that unifies object-level and pixel-level perception thro…

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