English(EN) GenScale: A Benchmark for Relative Object Scale in Image Generation and Editing

新的GenScale基准测试揭示图像生成器在物体尺度方面存在困难

作者 PulseAugur 编辑部 · [1 个来源] · 2026-09-02 04:00

研究人员推出了一项名为GenScale的新基准测试，旨在评估图像生成和编辑系统中相对物体尺度的准确性。该基准测试包含900个图像条目和超过1600个跨各种生成任务的成对尺度关系。为了解决观察到的尺度不准确问题，还开发了一个名为Rescale的模型无关后处理代理，该代理在不改变原始生成器的情况下，持续提高了生成和编辑图像中物体尺度的可信度。 AI

影响该基准测试和后处理工具可能会推动AI生成图像的真实性和准确性方面的改进，特别是在物体比例方面。

排序理由该集群描述了一个新的学术基准测试和相关的评估图像生成能力的工具。[lever_c_demoted from research: ic=1 ai=1.0]

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报道来源 [1]

arXiv cs.CV TIER_1 English(EN) · Lingxiao Li, Max Whitton, Ledell Wu, Boqing Gong · 2026-09-02 04:00

GenScale：图像生成与编辑中相对物体尺度的基准测试

arXiv:2609.00525v1 Announce Type: new Abstract: Modern image generation and editing systems can produce photorealistic, prompt-aligned images, but still often render familiar objects at implausible relative sizes. To measure this failure mode, we introduce GenScale, a benchmark a…

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报道来源 [1]

GenScale：图像生成与编辑中相对物体尺度的基准测试

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