CatalogStitch: 一种面向目录图像生成的维度感知和遮挡保留物体合成方法
CatalogStitch: Dimension-Aware and Occlusion-Preserving Object Compositing for Catalog Image Generation
AI总结：
CatalogStitch通过自动化修正遮挡元素和适应不同尺寸的产品，简化了目录图像生成流程，提升生成效率和质量。
摘要：
生成式物体合成方法在无缝插入物体到场景中表现出色。然而，当应用于真实世界目录图像生成时，这些方法需要繁琐的手动干预：用户必须在产品尺寸不同时手动调整掩码，并在生成后 painstakingly 恢复被遮挡的元素。我们提出了CatalogStitch，一套模型无关的技术，自动化这些修正，使内容创作更易于用户。我们的维度感知掩码计算算法自动调整目标区域以适应不同尺寸的产品；用户只需提供产品图像和背景，无需手动调整掩码。我们的遮挡感知混合恢复方法保证像素级保留遮挡元素，消除后期编辑流程。我们还引入了CatalogStitch-Eval，一个包含58个示例的基准测试集，涵盖纵横比不匹配和遮挡密集的目录场景，以及补充的PDF和HTML查看器。我们使用三种最先进的合成模型（ObjectStitch、OmniPaint和InsertAnything）评估我们的技术，展示了在多样化目录场景中的一致改进。通过减少手动干预和自动化繁琐的修正，我们的方法将生成式合成转化为一种实用的、适合人类的工具，用于生产目录工作流程。
英文摘要：
Generative object compositing methods have shown remarkable ability to seamlessly insert objects into scenes. However, when applied to real-world catalog image generation, these methods require tedious manual intervention: users must carefully adjust masks when product dimensions differ, and painstakingly restore occluded elements post-generation. We present CatalogStitch, a set of model-agnostic techniques that automate these corrections, enabling user-friendly content creation. Our dimension-aware mask computation algorithm automatically adapts the target region to accommodate products with different dimensions; users simply provide a product image and background, without manual mask adjustments. Our occlusion-aware hybrid restoration method guarantees pixel-perfect preservation of occluding elements, eliminating post-editing workflows. We additionally introduce CatalogStitch-Eval, a 58-example benchmark covering aspect-ratio mismatch and occlusion-heavy catalog scenarios, together with supplementary PDF and HTML viewers. We evaluate our techniques with three state-of-the-art compositing models (ObjectStitch, OmniPaint, and InsertAnything), demonstrating consistent improvements across diverse catalog scenarios. By reducing manual intervention and automating tedious corrections, our approach transforms generative compositing into a practical, human-friendly tool for production catalog workflows.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
