This review organizes literature on large multimodal models and object-centric vision into four themes—understanding, referring segmentation, editing, and generation—while summarizing paradigms, strategies, and challenges like instance permanence and consistent interaction.
Grasp any region: Towards precise, contextual pixel understanding for multimodal llms
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LMMs Meet Object-Centric Vision: Understanding, Segmentation, Editing and Generation
This review organizes literature on large multimodal models and object-centric vision into four themes—understanding, referring segmentation, editing, and generation—while summarizing paradigms, strategies, and challenges like instance permanence and consistent interaction.
- ClaimDiff-RL: Fine-Grained Caption Reinforcement Learning through Visual Claim Comparison
- Vision-OPD: Learning to See Fine Details for Multimodal LLMs via On-Policy Self-Distillation