Boosting Diffusion Models with Moving Average Sampling in Frequency Domain

Y Qian, Q Cai, Y Pan, Y Li, T Yao… - Proceedings of the …, 2024 - openaccess.thecvf.com
Diffusion models have recently brought a powerful revolution in image generation. Despite
showing impressive generative capabilities most of these models rely on the current sample …

Debias the training of diffusion models

H Yu, L Shen, J Huang, M Zhou, H Li… - arXiv preprint arXiv …, 2023 - arxiv.org
Diffusion models have demonstrated compelling generation quality by optimizing the
variational lower bound through a simple denoising score matching loss. In this paper, we …

Unmasking Bias in Diffusion Model Training

H Yu, L Shen, J Huang, H Li, F Zhao - European Conference on Computer …, 2024 - Springer
Denoising diffusion models have emerged as a dominant approach for image generation,
however they still suffer from slow convergence in training and color shift issues in sampling …

Score-based Generative Models with Adaptive Momentum

Z Wen, X Deng, P Luo, T Sun, D Li - arXiv preprint arXiv:2405.13726, 2024 - arxiv.org
Score-based generative models have demonstrated significant practical success in data-
generating tasks. The models establish a diffusion process that perturbs the ground truth …

[图书][B] Computer Vision-ECCV 2024: 18th European Conference, Milan, Italy, September 29-October 4, 2024, Proceedings, Part XXIV.

A Leonardis - 2024 - books.google.com
The multi-volume set of LNCS books with volume numbers 15059 up to 15147 constitutes
the refereed proceedings of the 18th European Conference on Computer Vision, ECCV …

Enhancing Histopathology Image Generation with Diffusion Generative Models: A Comprehensive Study

D Thakkar - 2024 - spectrum.library.concordia.ca
The field of histopathology faces significant challenges due to the limited availability of data,
which is often not publicly accessible due to privacy issues. The scarcity of high-quality …