.png){kind=icon}
返回
ControlMat: A Controlled Generative Approach to Material Capture
.png){kind=icon}
OA
AI
DOI：10.1145/3688830.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Material reconstruction from a photograph is a key component of 3D content creation democratization. We propose to formulate this ill-posed problem as a controlled synthesis one, leveraging the recent progress in generative deep networks. We present ControlMat, a method which, given a single photograph with uncontrolled illumination as input, conditions a diffusion model to generate plausible, tileable, high-resolution physically-based digital materials. We carefully analyze the behavior of diffusion models for multi-channel outputs, adapt the sampling process to fuse multi-scale information and introduce rolled diffusion to enable both tileability and patched diffusion for high-resolution outputs. Our generative approach further permits exploration of a variety of materials that could correspond to the input image, mitigating the unknown lighting conditions. We show that our approach outperforms recent inference and latent-space optimization methods, and we carefully validate our diffusion process design choices.
Keyword:
Computing methodologies
Appearance and texture representations
期刊
IF:
9.5
论文数:
4.7K
被引数:
3.6W
机构
引用论文
.png){kind=icon}
Sensorless Control of Z Source Inverter fed BLDC Motor Drive by FOC - DTC Hybrid Control Strategy Using Fuzzy Logic Controller采用模糊逻辑控制器的foc-dtc混合控制策略的Z源逆变器馈电BLDC电机驱动的无传感器控制
PREAI
分享收藏分享收藏
查看更多内容