FlexiTex: Enhancing Texture Generation with Visual Guidance
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.
66ecd7cf0d9e2833cec195b0
DaDong Jiang
66ecd7cf0d9e2833cec195b1
Xianghui Yang
claimed_verified
2025-01-23T09:22:09.108Z
647d9e881a1fcad2fdbf4954
/avatars/92ee8727d5c9063d852d3537b7690843.svg
SeanYoung
user
SeanYoungxh
66ecd7cf0d9e2833cec195b2
Zibo Zhao
admin_assigned
2024-09-20T09:38:53.369Z
62d8ce11c60d1450a1ed8795
/avatars/26f1ca693ad7106be0f2f469070d8500.svg
zibo.zhao
user
cocacola
66ecd7cf0d9e2833cec195b3
Sheng Zhang
66ecd7cf0d9e2833cec195b4
Jiaao Yu
admin_assigned
2024-09-20T09:39:16.562Z
648d83cf0c223ec38bd80eeb
/avatars/6b829c630b1b5bb7b4cac1a0d906dde8.svg
yujiaao
user
jiaaoyu
66ecd7cf0d9e2833cec195b5
Zeqiang Lai
admin_assigned
2024-09-20T09:39:22.899Z
63044b89eedc089484c995ad
https://cdn-avatars.huggingface.co/v1/production/uploads/no-auth/T4mOIQLaQdM5_oviaw_Cp.png
Zeqiang Lai
user
ZeqiangLai
66ecd7cf0d9e2833cec195b6
Shaoxiong Yang
admin_assigned
2024-09-20T09:39:35.151Z
6461f5ecddb3aaa43c8bfa3d
/avatars/29166b401aa9fa30f90254f3388bc169.svg
yangshaoxiong
user
ysx007
66ecd7cf0d9e2833cec195b7
Chunchao Guo
66ecd7cf0d9e2833cec195b8
Xiaobo Zhou
admin_assigned
2024-09-20T09:39:56.701Z
64658fd5c2037e5948067a8a
/avatars/6ead395b2560d42739b52f55a5042376.svg
Zhou Xiaobo
user
zouxb009
66ecd7cf0d9e2833cec195b9
Zhihui Ke
FlexiTex: Enhancing Texture Generation with Visual Guidance
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 generates high-quality textures using visual guidance to enhance text prompts and maintain consistency.
text-to-image diffusion models Visual Guidance Enhancement module Direction-Aware Adaptation module Janus problem semantically global consistency texture generation