正文：
近日，人工智能领域再传佳讯，来自新加坡国立大学的研究团队提出了一种名为“Paints-UNDO”的先进AI模型，该模型能够通过一张完成的作品，“重现”整个绘画过程。这项技术不仅在视觉上还原了画家的创作步骤，还为艺术教学和数字艺术的发展带来了新的可能性。
Paints-UNDO模型的核心在于其能够学习并模拟人类画家的绘画过程。研究人员通过在合成数据和人类画师绘画视频上训练时序模型，首次实现了让扩散模型生成绘画过程。这一技术突破不仅填补了AI在艺术创作领域的空白，也为艺术教育提供了新的工具。
该模型的成功，得益于其创新的时序注意力机制和艺术品复制网络。时序注意力机制能够确保绘画序列的平滑过渡和连续性，而艺术品复制网络则能够处理任意帧的图像输入，灵活控制绘画过程的生成。这些技术上的创新，使得Paints-UNDO能够从一张完成的作品中，逐步还原出创作的全过程。
此外，研究人员还利用预训练的Motion Model和少量特定画师的绘画序列数据，训练Motion LoRA模型，学习画师的绘画技法。这一方法不仅能够复制不同画家的风格，还能够让AI模仿特定画家的技法，为艺术创作带来新的可能性。
Paints-UNDO模型的发布，不仅在AI生成内容（AIGC）领域引起了震动，也为艺术教育带来了新的教学工具。通过这一模型，学生不仅能够学习到绘画技巧，还能够直观地看到一幅作品是如何一步步完成的，从而更加深入地理解艺术创作的过程。
总的来说，Paints-UNDO模型的问世，标志着AI在艺术创作和教学领域迈出了重要的一步。随着技术的不断进步，未来AI在艺术创作中的应用前景将更加广阔。
英语如下：
News Title: “AI Breakthrough: Reconstructing the Entire Painting Process from a Single Image”
Keywords: AI Painting, Process Reconstruction, Innovative Research Paper
News Content:
Recent advancements in the field of artificial intelligence have seen another significant development, as a research team from the National University of Singapore unveiled an advanced AI model named “Paints-UNDO.” This model is capable of reconstructing the entire painting process from a single completed work of art. Not only does this technology visually reconstruct the artist’s creative steps, but it also opens up new possibilities for art education and the development of digital art.
The core of the Paints-UNDO model lies in its ability to learn and mimic the painting process of human artists. Researchers trained a temporal model on synthetic data and video recordings of human painters, marking the first time a diffusion model has been able to generate the painting process. This technological breakthrough not only fills a gap in AI’s capabilities in the realm of artistic creation but also provides a new tool for art education.
The success of the model is attributed to its innovative temporal attention mechanism and artwork replication network. The temporal attention mechanism ensures a smooth transition and continuity in the painting sequence, while the artwork replication network handles arbitrary frame inputs and flexibly controls the generation of the painting process. These technological innovations enable Paints-UNDO to gradually reconstruct the entire creative process from a single completed work of art.
Furthermore, the researchers utilized a pre-trained Motion Model and a small amount of specific painter’s painting sequence data to train a Motion LoRA model, learning the painter’s techniques. This method not only allows for the replication of different artists’ styles but also enables AI to mimic the techniques of specific painters, opening up new possibilities for artistic creation.
The release of the Paints-UNDO model has not only caused a stir in the AI Generated Content (AIGC) field but also introduces a new teaching tool for art education. Through this model, students can not only learn painting techniques but also see in real-time how a piece of art is gradually completed, thus gaining a deeper understanding of the artistic creation process.
In summary, the emergence of the Paints-UNDO model marks a significant step forward for AI in the fields of artistic creation and education. With ongoing technological advancements, the potential for AI in artistic creation looks promising.
【来源】https://www.jiqizhixin.com/articles/2024-07-30-2
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