On Analyzing Generative and Denoising Capabilities of Diffusion-based Deep Generative Models

31 May 2022

Papers citing "On Analyzing Generative and Denoising Capabilities of Diffusion-based Deep Generative Models"

21 / 21 papers shown

Title
Devil is in the Details: Density Guidance for Detail-Aware Generation with Flow Models Rafał Karczewski Markus Heinonen Vikas K. Garg DiffM 42 0 0 09 Feb 2025
Flexiffusion: Segment-wise Neural Architecture Search for Flexible Denoising Schedule Hongtao Huang Xiaojun Chang Lina Yao 28 0 0 26 Sep 2024
GeoGuide: Geometric guidance of diffusion models Mateusz Poleski Jacek Tabor P. Spurek 34 1 0 17 Jul 2024
Beta Sampling is All You Need: Efficient Image Generation Strategy for Diffusion Models using Stepwise Spectral Analysis Haeil Lee Han S. Lee Seoyeon Gye Junmo Kim DiffM 37 2 0 16 Jul 2024
Denoising Task Difficulty-based Curriculum for Training Diffusion Models Jin-Young Kim Hyojun Go Soonwoo Kwon Hyun-Gyoon Kim DiffM 46 6 0 15 Mar 2024
Fine-grained Forecasting Models Via Gaussian Process Blurring Effect Sepideh Koohfar Laura Dietz DiffM AI4TS 13 0 0 21 Dec 2023
Improving Efficiency of Diffusion Models via Multi-Stage Framework and Tailored Multi-Decoder Architectures Huijie Zhang Yifu Lu Ismail R. Alkhouri S. Ravishankar Dogyoon Song Qing Qu 24 9 0 14 Dec 2023
Clockwork Diffusion: Efficient Generation With Model-Step Distillation A. Habibian Amir Ghodrati Noor Fathima Guillaume Sautière Risheek Garrepalli Fatih Porikli Jens Petersen 15 7 0 13 Dec 2023
ToddlerDiffusion: Flash Interpretable Controllable Diffusion Model Eslam Mohamed Bakr Liangbing Zhao Vincent Tao Hu Matthieu Cord Patrick Pérez Mohamed Elhoseiny 22 0 0 24 Nov 2023
Continual Learning of Diffusion Models with Generative Distillation Sergi Masip Pau Rodriguez Tinne Tuytelaars Gido M. van de Ven VLM DiffM 21 7 0 23 Nov 2023
DiffSCI: Zero-Shot Snapshot Compressive Imaging via Iterative Spectral Diffusion Model Zhenghao Pan Haijin Zeng Jiezhang Cao Kai Zhang Yongyong Chen 8 5 0 19 Nov 2023
Expanding Expressiveness of Diffusion Models with Limited Data via Self-Distillation based Fine-Tuning Jiwan Hur Jaehyun Choi Gyojin Han Dong-Jae Lee Junmo Kim 22 4 0 02 Nov 2023
AutoDiffusion: Training-Free Optimization of Time Steps and Architectures for Automated Diffusion Model Acceleration Lijiang Li Huixia Li Xiawu Zheng Jie Wu Xuefeng Xiao Rui Wang Min Zheng Xin Pan Fei Chao R. Ji 77 35 0 19 Sep 2023
DiffDance: Cascaded Human Motion Diffusion Model for Dance Generation Qiaosong Qi Le Zhuo Aixi Zhang Yue Liao Fei Fang Si Liu Shuicheng Yan 11 22 0 05 Aug 2023
On the Design Fundamentals of Diffusion Models: A Survey Ziyi Chang G. Koulieris Hubert P. H. Shum DiffM 27 52 0 07 Jun 2023
Denoising Diffusion Models for Plug-and-Play Image Restoration Yuanzhi Zhu K. Zhang Jingyun Liang Jiezhang Cao B. Wen Radu Timofte Luc Van Gool DiffM 58 197 0 15 May 2023
Exploring Continual Learning of Diffusion Models Michal Zajac Kamil Deja Anna Kuzina Jakub M. Tomczak Tomasz Trzciñski Florian Shkurti Piotr Milo's DiffM 14 11 0 27 Mar 2023
A Lipschitz Bandits Approach for Continuous Hyperparameter Optimization Yasong Feng Weijian Luo Yimin Huang Tianyu Wang 13 8 0 03 Feb 2023
A Residual Diffusion Model for High Perceptual Quality Codec Augmentation Noor Fathima Ghouse Jens Petersen Auke Wiggers Tianlin Xu Guillaume Sautière DiffM 24 21 0 13 Jan 2023
Diffusion Models in Vision: A Survey Florinel-Alin Croitoru Vlad Hondru Radu Tudor Ionescu M. Shah DiffM VLM MedIm 191 1,133 0 10 Sep 2022
Improving neural networks by preventing co-adaptation of feature detectors Geoffrey E. Hinton Nitish Srivastava A. Krizhevsky Ilya Sutskever Ruslan Salakhutdinov VLM 243 7,620 0 03 Jul 2012