English(EN) From Diffusion to Rectified Flow: Rethinking Text-Based Segmentation

研究人员使用校正流而非扩散模型重新思考基于文本的分割

作者 PulseAugur 编辑部 · [2 个来源] · 2026-05-06 07:40

研究人员开发了RLFSeg，一个利用校正流进行基于文本的图像分割的新框架。该方法旨在通过学习从图像到分割掩码的直接映射来改进扩散模型，绕过了生成过程。据报道，该框架在零样本场景下实现了更高的准确性，并通过标签细化和自适应采样即使在单次推理步骤中也能提高性能。 AI

影响引入了一种新颖的基于文本的图像分割方法，可以增强零样本能力和推理效率。

排序理由这是一篇发表在arXiv上的研究论文，详细介绍了一个新的图像分割框架。

AI 生成摘要 · Google Gemini · 来自 2 个来源。我们如何撰写摘要 →

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arXiv cs.CV TIER_1 English(EN) · Zishen Qu, Xuesong Li, Haijian Gu, Hongwei Kang, Quan Meng, Tianrui Niu, Xin Yang, Ruidong Pan · 2026-05-07 04:00

从扩散模型到修正流：重新思考基于文本的分割

arXiv:2605.04590v1 Announce Type: new Abstract: Text-based image segmentation aims to delineate object boundaries within an image from text prompts, offering higher flexibility and broader application scope compared to traditional fixed-category segmentation tasks. Recent studies…
arXiv cs.CV TIER_1 English(EN) · Ruidong Pan · 2026-05-06 07:40

从扩散模型到修正流：重新思考基于文本的分割

Text-based image segmentation aims to delineate object boundaries within an image from text prompts, offering higher flexibility and broader application scope compared to traditional fixed-category segmentation tasks. Recent studies have shown that diffusion models (e.g., Stable …