LMMs 与以物体为中心的视觉：理解、分割、编辑和生成
LMMs Meet Object-Centric Vision: Understanding, Segmentation, Editing and Generation
AI总结：
本文探讨了LMMs与以物体为中心的视觉结合，总结了在理解、分割、编辑和生成方面的新进展，提出了开放挑战和未来方向。
摘要：
大型多模态模型（LMMs）在通用视觉-语言理解方面取得了显著进展，但仍然在需要精确物体级定位、细粒度空间推理和可控视觉操作的任务中受限。以物体为中心的视觉提供了一个原则性的框架，通过促进对视觉实体的显式表示和操作，将多模态系统从全局场景理解扩展到物体级理解、分割、编辑和生成。本文综述了LMMs与以物体为中心的视觉交汇处的最新进展。我们将文献分为四个主要主题：以物体为中心的视觉理解、以物体为中心的指称分割、以物体为中心的视觉编辑和以物体为中心的视觉生成。我们进一步总结了支持这些能力的关键建模范式、学习策略和评估协议。最后，我们讨论了开放挑战和未来方向，包括鲁棒的实例持久性、细粒度空间控制、一致的多步交互、统一的跨任务建模和在分布偏移下的可靠基准测试。我们希望本文能为可扩展、精确和可信的以物体为中心的多模态系统的发展提供结构化的视角。
英文摘要：
Large Multimodal Models (LMMs) have achieved remarkable progress in general-purpose vision--language understanding, yet they remain limited in tasks requiring precise object-level grounding, fine-grained spatial reasoning, and controllable visual manipulation. In particular, existing systems often struggle to identify the correct instance, preserve object identity across interactions, and localize or modify designated regions with high precision. Object-centric vision provides a principled framework for addressing these challenges by promoting explicit representations and operations over visual entities, thereby extending multimodal systems from global scene understanding to object-level understanding, segmentation, editing, and generation. This paper presents a comprehensive review of recent advances at the convergence of LMMs and object-centric vision. We organize the literature into four major themes: object-centric visual understanding, object-centric referring segmentation, object-centric visual editing, and object-centric visual generation. We further summarize the key modeling paradigms, learning strategies, and evaluation protocols that support these capabilities. Finally, we discuss open challenges and future directions, including robust instance permanence, fine-grained spatial control, consistent multi-step interaction, unified cross-task modeling, and reliable benchmarking under distribution shift. We hope this paper provides a structured perspective on the development of scalable, precise, and trustworthy object-centric multimodal systems.
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。
