Make-it-Real: Unleashing Large Multimodal Model's Ability for Painting 3D Objects with Realistic Materials

arXiv:2404.16829v1 Announce Type: new
Abstract: Physically realistic materials are pivotal in augmenting the realism of 3D assets across various applications and lighting conditions. However, existing 3D assets and generative models often lack authentic material properties. Manual assignment of materials using graphic software is a tedious and time-consuming task. In this paper, we exploit advancements in Multimodal Large Language Models (MLLMs), particularly GPT-4V, to present a novel approach, Make-it-Real: 1) We demonstrate that GPT-4V can effectively recognize and describe materials, allowing …

3d objects abstract applications arxiv authentic cs.ai cs.cl cs.cv generative generative models graphic however lighting material materials multimodal multimodal model objects painting pivotal software type