FlexiTex：透過視覺引導增強紋理生成

摘要

最近的紋理生成方法取得了令人印象深刻的成果，這歸因於它們從大規模文本到圖像擴散模型中利用的強大生成先驗。然而，抽象的文本提示在提供全局紋理或形狀信息方面存在限制，這導致紋理生成方法產生模糊或不一致的模式。為了應對這一挑戰，我們提出了FlexiTex，通過視覺引導嵌入豐富信息以生成高質量紋理。FlexiTex的核心是視覺引導增強模組，它從視覺引導中納入更具體的信息，以減少文本提示中的歧義並保留高頻細節。為了進一步增強視覺引導，我們引入了一個自動設計方向提示的Direction-Aware Adaptation模組，根據不同的相機姿勢避免了Janus問題並保持語義上的全局一致性。受益於視覺引導，FlexiTex產生了定量和定性上令人滿意的結果，展示了其推進現實應用中紋理生成的潛力。

English

Recent texture generation methods achieve impressive results due to the powerful generative prior they leverage from large-scale text-to-image diffusion models. However, abstract textual prompts are limited in providing global textural or shape information, which results in the texture generation methods producing blurry or inconsistent patterns. To tackle this, we present FlexiTex, embedding rich information via visual guidance to generate a high-quality texture. The core of FlexiTex is the Visual Guidance Enhancement module, which incorporates more specific information from visual guidance to reduce ambiguity in the text prompt and preserve high-frequency details. To further enhance the visual guidance, we introduce a Direction-Aware Adaptation module that automatically designs direction prompts based on different camera poses, avoiding the Janus problem and maintaining semantically global consistency. Benefiting from the visual guidance, FlexiTex produces quantitatively and qualitatively sound results, demonstrating its potential to advance texture generation for real-world applications.

FlexiTex：透過視覺引導增強紋理生成

FlexiTex: Enhancing Texture Generation with Visual Guidance

摘要

Summary

Support

Support