Zero-Shot Multi-Modal Artist-Controlled Retrieval and Exploration of 3D Object Sets

• URL: http://arxiv.org/abs/2209.00682v1
• Date: Thu, 1 Sep 2022 18:36:43 GMT
• Title: Zero-Shot Multi-Modal Artist-Controlled Retrieval and Exploration of 3D Object Sets
• Authors: Kristofer Schlachter, Benjamin Ahlbrand, Zhu Wang, Valerio Ortenzi, Ken Perlin
• Abstract summary: High-quality 3D asset retrieval from multi-modal inputs, including 2D sketches, images and text. We use CLIP as it provides a bridge to higher-level latent features. We use these features to perform a multi-modality fusion to address the lack of artistic control that affects common data-driven approaches.
• Score: 4.2880616924515
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: When creating 3D content, highly specialized skills are generally needed to design and generate models of objects and other assets by hand. We address this problem through high-quality 3D asset retrieval from multi-modal inputs, including 2D sketches, images and text. We use CLIP as it provides a bridge to higher-level latent features. We use these features to perform a multi-modality fusion to address the lack of artistic control that affects common data-driven approaches. Our approach allows for multi-modal conditional feature-driven retrieval through a 3D asset database, by utilizing a combination of input latent embeddings. We explore the effects of different combinations of feature embeddings across different input types and weighting methods.

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