Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Chambon, Thomas"'
Publikováno v:
SIGGRAPH 2023 Conference Proceedings
We derive a minimalist but powerful deterministic denoising-diffusion model. While denoising diffusion has shown great success in many domains, its underlying theory remains largely inaccessible to non-expert users. Indeed, an understanding of gradua
Externí odkaz:
http://arxiv.org/abs/2305.03486
Our objective is to compute a textural loss that can be used to train texture generators with multiple material channels typically used for physically based rendering such as albedo, normal, roughness, metalness, ambient occlusion, etc. Neural textur
Externí odkaz:
http://arxiv.org/abs/2105.13012
Publikováno v:
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2021
We address the problem of computing a textural loss based on the statistics extracted from the feature activations of a convolutional neural network optimized for object recognition (e.g. VGG-19). The underlying mathematical problem is the measure of
Externí odkaz:
http://arxiv.org/abs/2006.07229
Autor:
Chambon, Thomas1 (AUTHOR) thomas.chambon1@univ-lr.fr, Guillaume, Jean-Loup1 (AUTHOR), Lallement, Jeanne2 (AUTHOR)
Publikováno v:
Entropy. Mar2023, Vol. 25 Issue 3, p439. 14p.
