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Make It Count: Text-to-Image Generation with an Accurate Number of Objects
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2026-01-24 16:52:16
raw text
Make It Count Make It Count: Text-to-Image Generation with an Accurate Number of Objects Lital Binyamin 1 , Yoad Tewel 2,3 , Hilit Segev 1 , Eran Hirsch 1 , Royi Rassin 1 , Gal Chechik 1,2 1 Bar-Ilan University, 2 NVIDIA, 3 Tel-Aviv University CVPR 2025 arXiv Code CountGen generates the correct number of objects specified in the input prompt while maintaining a natural layout that aligns with the prompt. Examples of Text-to-Image Generation with CountGen Abstract Despite the unprecedented success of text-to-image diffusion models, controlling the number of depicted objects using text is surprisingly hard. This is important for various applications from technical documents, to children’s books to illustrating cooking recipes. Generating object-correct counts is fundamentally challenging because the generative model needs to keep a sense of separate identity for every instance of the object, even if several obj...
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