Diffusion Model

Diffusion models are generative models that create data by reversing a noise-diffusion process, aiming to generate high-quality samples from complex distributions. Current research focuses on improving efficiency through techniques like stochastic Runge-Kutta methods and dynamic model architectures (e.g., Dynamic Diffusion Transformer), as well as enhancing controllability and safety via methods such as classifier-free guidance and reinforcement learning from human feedback. These advancements are significantly impacting various fields, including medical imaging, robotics, and artistic creation, by enabling novel applications in image generation, inverse problem solving, and multi-modal data synthesis.

Papers

November 15, 2024

The Unreasonable Effectiveness of Guidance for Diffusion Models
Tim Kaiser, Nikolas Adaloglou, Markus Kollmann
Diffusion Model Temporal Dependency Human Guidance Image Fidelity Guidance Law Auxiliary Model
ColorEdit: Training-free Image-Guided Color editing with diffusion model
Xingxi Yin, Zhi Li, Jingfeng Zhang, Chenglin Li, Yin Zhang
Diffusion Model Image Synthesis Image Editing Color Correction Cross Attention Block
Adaptive Non-Uniform Timestep Sampling for Diffusion Model Training
Myunsoo Kim, Donghyeon Ki, Seong-Woong Shim, Byung-Jun Lee
Diffusion Model Stochastic Gradient Sampling Technique Diffusion Model Architecture Step Sampling

November 14, 2024

Golden Noise for Diffusion Models: A Learning Framework
Zikai Zhou, Shitong Shao, Lichen Bai, Zhiqiang Xu, Bo Han, Zeke Xie
Diffusion Model Text to Image Diffusion Model Gaussian Noise Learning Framework Diffusion Sampling Background Noise
EEG-Based Speech Decoding: A Novel Approach Using Multi-Kernel Ensemble Diffusion Models
Soowon Kim, Ha-Na Jo, Eunyeong Ko
Diffusion Model Novel Approach Ensemble Method Brain Signal Neural Signal Kernel Learning Conditional Autoencoder

November 13, 2024

Inconsistencies In Consistency Models: Better ODE Solving Does Not Imply Better Samples
Noël Vouitsis, Rasa Hosseinzadeh, Brendan Leigh Ross, Valentin Villecroze, Satya Krishna Gorti, Jesse C. Cresswell, Gabriel Loaiza-Ganem
Diffusion Model Consistency Model Hard to Easy Inconsistency Sample Quality
Offline Adaptation of Quadruped Locomotion using Diffusion Models
Reece O'Mahoney, Alexander L. Mitchell, Wanming Yu, Ingmar Posner, Ioannis Havoutis
Diffusion Model Human Like Locomotion Behavior Diffusion Based Quadrupedal Locomotion Goal Conditioned Quadruped Locomotion Locomotion Strategy
Physics Informed Distillation for Diffusion Models
Joshua Tian Jin Tee, Kang Zhang, Hee Suk Yoon, Dhananjaya Nagaraja Gowda, Chanwoo Kim, Chang D. Yoo
Diffusion Model Implicit Model Distillation Framework Probability Flow ODE

November 12, 2024

Scaling Properties of Diffusion Models for Perceptual Tasks
Rahul Ravishankar, Zeeshan Patel, Jathushan Rajasegaran, Jitendra Malik
Diffusion Model Optical Flow Image to Image Translation Visual Perception Perception Task Scaling Behavior
Structured Pattern Expansion with Diffusion Models
Marzia Riso, Giuseppe Vecchio, Fabio Pellacini
Diffusion Model Complex Pattern Stationary Distribution Pre Trained Image Diffusion Model
Novel View Synthesis with Pixel-Space Diffusion Models
Noam Elata, Bahjat Kawar, Yaron Ostrovsky-Berman, Miriam Farber, Ron Sokolovsky
Diffusion Model Generative Model Novel View Synthesis Training Scheme
Unraveling the Connections between Flow Matching and Diffusion Probabilistic Models in Training-free Conditional Generation
Kaiyu Song, Hanjiang Lai
Diffusion Model Diffusion Explainer Probabilistic Model Flow Matching New Connection Conditional Generation High Quality Generation
Tracing the Roots: Leveraging Temporal Dynamics in Diffusion Trajectories for Origin Attribution
Andreas Floros, Seyed-Mohsen Moosavi-Dezfooli, Pier Luigi Dragotti
Diffusion Model Diffusion Explainer Pre Trained Diffusion Model Handwritten Trajectory Temporal Dynamic SHUSS Root Exploration Term Diffusion Trajectory Discriminative Classifier

November 11, 2024

Score-based generative diffusion with "active" correlated noise sources
Alexandra Lamtyugina, Agnish Kumar Behera, Aditya Nandy, Carlos Floyd, Suriyanarayanan Vaikuntanathan
Diffusion Model Generative Process Temporal Correlation Generative Diffusion Robust Generative Active Matter Noise Source
Add-it: Training-Free Object Insertion in Images With Pretrained Diffusion Models
Yoad Tewel, Rinon Gal, Dvir Samuel Yuval Atzmon, Lior Wolf, Gal Chechik
Diffusion Model Pre Trained Attention Mechanism Object Insertion Semantic Image Editing Object Placement Object Placement Assessment
OmniEdit: Building Image Editing Generalist Models Through Specialist Supervision
Cong Wei, Zheyang Xiong, Weiming Ren, Xinrun Du, Ge Zhang, Wenhu Chen
Diffusion Model Image Editing Social Medium Site Reddit Expertise Level
Edify Image: High-Quality Image Generation with Pixel Space Laplacian Diffusion Models
NVIDIA: Yuval Atzmon, Maciej Bala, Yogesh Balaji, Tiffany Cai, Yin Cui, Jiaojiao Fan, Yunhao Ge, Siddharth Gururani, Jacob Huffman, Ronald Isaac, Pooya Jannaty, Tero Karras, Grace Lam, J. P. Lewis, Aaron Licata, Yen-Chen Lin, Ming-Yu Liu, Qianli Ma, Arun Mallya, Ashlee Martino-Tarr, Doug Mendez, Seungjun Nah, Chris Pruett, Fitsum Reda, Jiaming Song, Ting-Chun Wang, Fangyin Wei, Xiaohui Zeng, Yu Zeng, Qinsheng Zhang
Diffusion Model Image Generation Image Editing Text to Image Synthesis Photorealistic Image
DiffSR: Learning Radar Reflectivity Synthesis via Diffusion Model from Satellite Observations
Xuming He, Zhiwang Zhou, Wenlong Zhang, Xiangyu Zhao, Hao Chen, Shiqi Chen, Lei Bai
Diffusion Model Diffusion Based Radar Data Satellite Observation Radar Reflectivity

November 10, 2024

Using Diffusion Models as Generative Replay in Continual Federated Learning -- What will Happen?
Yongsheng Mei, Liangqi Yuan, Dong-Jun Han, Kevin S. Chan, Christopher G. Brinton, Tian Lan
LeArning Abstract Diffusion Model Generative Adversarial Network Conditional Diffusion Model Decentralized Learning Continuous Learning Generative Replay Federated Continual Learning
Detecting AutoEncoder is Enough to Catch LDM Generated Images
Dmitry Vesnin, Dmitry Levshun, Andrey Chechulin
Diffusion Model Supervised Autoencoder Latent Diffusion Model Fake Image Autoencoder Model Diffusion Autoencoder

Diffusion Model

Papers

The Unreasonable Effectiveness of Guidance for Diffusion Models

ColorEdit: Training-free Image-Guided Color editing with diffusion model

Adaptive Non-Uniform Timestep Sampling for Diffusion Model Training

Golden Noise for Diffusion Models: A Learning Framework

EEG-Based Speech Decoding: A Novel Approach Using Multi-Kernel Ensemble Diffusion Models

Inconsistencies In Consistency Models: Better ODE Solving Does Not Imply Better Samples

Offline Adaptation of Quadruped Locomotion using Diffusion Models

Physics Informed Distillation for Diffusion Models

Scaling Properties of Diffusion Models for Perceptual Tasks

Structured Pattern Expansion with Diffusion Models

Novel View Synthesis with Pixel-Space Diffusion Models

Unraveling the Connections between Flow Matching and Diffusion Probabilistic Models in Training-free Conditional Generation

Tracing the Roots: Leveraging Temporal Dynamics in Diffusion Trajectories for Origin Attribution

Score-based generative diffusion with "active" correlated noise sources

Add-it: Training-Free Object Insertion in Images With Pretrained Diffusion Models

OmniEdit: Building Image Editing Generalist Models Through Specialist Supervision

Edify Image: High-Quality Image Generation with Pixel Space Laplacian Diffusion Models

DiffSR: Learning Radar Reflectivity Synthesis via Diffusion Model from Satellite Observations

Using Diffusion Models as Generative Replay in Continual Federated Learning -- What will Happen?

Detecting AutoEncoder is Enough to Catch LDM Generated Images