- See Also
- Gwern
-
Links
- “Long-Form Music Generation With Latent Diffusion”, Evans et al 2024
- “VASA-1: Lifelike Audio-Driven Talking Faces Generated in Real Time”, Xu et al 2024
- “Measuring Style Similarity in Diffusion Models”, Somepalli et al 2024
- “Is Model Collapse Inevitable? Breaking the Curse of Recursion by Accumulating Real and Synthetic Data”, Gerstgrasser et al 2024
- “TextCraftor: Your Text Encoder Can Be Image Quality Controller”, Li et al 2024
- “Improving Text-To-Image Consistency via Automatic Prompt Optimization”, Mañas et al 2024
- “SDXS: Real-Time One-Step Latent Diffusion Models With Image Conditions”, Song et al 2024
- “CMD: Efficient Video Diffusion Models via Content-Frame Motion-Latent Decomposition”, Yu et al 2024
- “ZigMa: Zigzag Mamba Diffusion Model”, Hu et al 2024
- “Atomically Accurate de Novo Design of Single-Domain Antibodies”, Bennett et al 2024
- “Sketch2Manga: Shaded Manga Screening from Sketch With Diffusion Models”, Lin et al 2024
- “ELLA: Equip Diffusion Models With LLM for Enhanced Semantic Alignment”, Hu et al 2024
- “Transparent Image Layer Diffusion Using Latent Transparency”, Zhang & Agrawala 2024
- “CartoonizeDiff: Diffusion-Based Photo Cartoonization Scheme”, Jeon et al 2024
- “Discovering Universal Semantic Triggers for Text-To-Image Synthesis”, Zhai et al 2024
- “AnimeDiffusion: Anime Diffusion Colorization”, Cao et al 2024
- “Why a Chinese Court’s Landmark Decision Recognising the Copyright for an AI-Generated Image Benefits Creators in This Nascent Field”, Shen 2024
- “Bridging the Gap: Sketch to Color Diffusion Model With Semantic Prompt Learning”, Wang et al 2024
- “GenCast: Diffusion-Based Ensemble Forecasting for Medium-Range Weather”, Price et al 2023
- “Training Stable Diffusion from Scratch Costs <$160k”, Stephenson & Seguin 2023
- “Generative AI Beyond LLMs: System Implications of Multi-Modal Generation”, Golden et al 2023
- “DreamTuner: Single Image Is Enough for Subject-Driven Generation”, Hua et al 2023
- “Rich Human Feedback for Text-To-Image Generation”, Liang et al 2023
- “ECLIPSE: A Resource-Efficient Text-To-Image Prior for Image Generations”, Patel et al 2023
- “Self-Conditioned Image Generation via Generating Representations”, Li et al 2023
- “Retrieving Conditions from Reference Images for Diffusion Models”, Tang et al 2023
- “Analyzing and Improving the Training Dynamics of Diffusion Models”, Karras et al 2023
- “DiffiT: Diffusion Vision Transformers for Image Generation”, Hatamizadeh et al 2023
- “Diffusion Models Without Attention”, Yan et al 2023
- “MicroCinema: A Divide-And-Conquer Approach for Text-To-Video Generation”, Wang et al 2023
- “AnyLens: A Generative Diffusion Model With Any Rendering Lens”, Voynov et al 2023
- “TextDiffuser-2: Unleashing the Power of Language Models for Text Rendering”, Chen et al 2023
- “MobileDiffusion: Subsecond Text-To-Image Generation on Mobile Devices”, Zhao et al 2023
- “Adversarial Diffusion Distillation”, Sauer et al 2023
- “Generative Models: What Do They Know? Do They Know Things? Let’s Find Out!”, Du et al 2023
- “Test-Time Adaptation of Discriminative Models via Diffusion Generative Feedback”, Prabhudesai et al 2023
- “Diffusion Model Alignment Using Direct Preference Optimization”, Wallace et al 2023
- “Concept Sliders: LoRA Adaptors for Precise Control in Diffusion Models”, Gandikota et al 2023
- “UFOGen: You Forward Once Large Scale Text-To-Image Generation via Diffusion GANs”, Xu et al 2023
- “I2VGen-XL: High-Quality Image-To-Video Synthesis via Cascaded Diffusion Models”, Zhang et al 2023
- “AnyText: Multilingual Visual Text Generation And Editing”, Tuo et al 2023
- “Idempotent Generative Network”, Shocher et al 2023
- “Beyond U: Making Diffusion Models Faster & Lighter”, Calvo-Ordonez et al 2023
- “CADS: Unleashing the Diversity of Diffusion Models through Condition-Annealed Sampling”, Sadat et al 2023
- “CommonCanvas: An Open Diffusion Model Trained With Creative-Commons Images”, Gokaslan et al 2023
- “Prompt-Specific Poisoning Attacks on Text-To-Image Generative Models”, Shan et al 2023
- “Generalization in Diffusion Models Arises from Geometry-Adaptive Harmonic Representation”, Kadkhodaie et al 2023
- “Emu: Enhancing Image Generation Models Using Photogenic Needles in a Haystack”, Dai et al 2023
- “Generating and Imputing Tabular Data via Diffusion and Flow-Based Gradient-Boosted Trees”, Jolicoeur-Martineau et al 2023
- “InstaFlow: One Step Is Enough for High-Quality Diffusion-Based Text-To-Image Generation”, Liu et al 2023
- “MetaDiff: Meta-Learning With Conditional Diffusion for Few-Shot Learning”, Zhang & Yu 2023
- “Provable Guarantees for Generative Behavior Cloning: Bridging Low-Level Stability and High-Level Behavior”, Block et al 2023
- “Diffusion Models Beat GANs on Image Classification”, Mukhopadhyay et al 2023
- “SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis”, Podell et al 2023
- “SDXL § Micro-Conditioning: Conditioning the Model on Image Size”, Podell et al 2023 (page 3 org stability)
- “DiffSketcher: Text Guided Vector Sketch Synthesis through Latent Diffusion Models”, Xing et al 2023
- “Semi-Implicit Denoising Diffusion Models (SIDDMs)”, Xu et al 2023
- “StyleTTS 2: Towards Human-Level Text-To-Speech through Style Diffusion and Adversarial Training With Large Speech Language Models”, Li et al 2023
- “Beyond Surface Statistics: Scene Representations in a Latent Diffusion Model”, Chen et al 2023
- “Exposing Flaws of Generative Model Evaluation Metrics and Their Unfair Treatment of Diffusion Models”, Stein et al 2023
- “StyleDrop: Text-To-Image Generation in Any Style”, Sohn et al 2023
- “Artificial Intelligence and Art: Identifying the Esthetic Judgment Factors That Distinguish Human & Machine-Generated Artwork”, Samo & Highhouse 2023
- “Spontaneous Symmetry Breaking in Generative Diffusion Models”, Raya & Ambrogioni 2023
- “Tree-Ring Watermarks: Fingerprints for Diffusion Images That Are Invisible and Robust”, Wen et al 2023
- “Generalizable Synthetic Image Detection via Language-Guided Contrastive Learning”, Wu et al 2023
- “Common Diffusion Noise Schedules and Sample Steps Are Flawed”, Lin et al 2023
- “Diffusart: Enhancing Line Art Colorization With Conditional Diffusion Models”, Carrillo et al 2023
- “Continual Diffusion: Continual Customization of Text-To-Image Diffusion With C-LoRA”, Smith et al 2023
- “Reference-Based Image Composition With Sketch via Structure-Aware Diffusion Model”, Kim et al 2023
- “Masked Diffusion Transformer Is a Strong Image Synthesizer”, Gao et al 2023
- “Prompting AI Art: An Investigation into the Creative Skill of Prompt Engineering”, Oppenlaender et al 2023
- “TRACT: Denoising Diffusion Models With Transitive Closure Time-Distillation”, Berthelot et al 2023
- “Consistency Models”, Song et al 2023
- “Understanding the Diffusion Objective As a Weighted Integral of ELBOs”, Kingma & Gao 2023
- “Adding Conditional Control to Text-To-Image Diffusion Models”, Zhang et al 2023
- “Glaze: Protecting Artists from Style Mimicry by Text-To-Image Models”, Shan et al 2023
- “Hard Prompts Made Easy: Gradient-Based Discrete Optimization for Prompt Tuning and Discovery”, Wen et al 2023
- “Dreamix: Video Diffusion Models Are General Video Editors”, Molad et al 2023
- “Imitating Human Behavior With Diffusion Models”, Pearce et al 2023
- “Msanii: High Fidelity Music Synthesis on a Shoestring Budget”, Maina 2023
- “Archisound: Audio Generation With Diffusion”, Schneider 2023
- “DIRAC: Neural Image Compression With a Diffusion-Based Decoder”, Goose et al 2023
- “Tune-A-Video: One-Shot Tuning of Image Diffusion Models for Text-To-Video Generation”, Wu et al 2022
- “Character-Aware Models Improve Visual Text Rendering”, Liu et al 2022
- “Diffusion Transformers (DiTs): Scalable Diffusion Models With Transformers”, Peebles & Xie 2022
- “Point·E: A System for Generating 3D Point Clouds from Complex Prompts”, Nichol et al 2022
- “The Stable Artist: Steering Semantics in Diffusion Latent Space”, Brack et al 2022
- “Multi-Concept Customization of Text-To-Image Diffusion”, Kumari et al 2022
- “Multi-Resolution Textual Inversion”, Daras & Dimakis 2022
- “Latent Video Diffusion Models for High-Fidelity Video Generation With Arbitrary Lengths”, He et al 2022
- “VectorFusion: Text-To-SVG by Abstracting Pixel-Based Diffusion Models”, Jain et al 2022
- “DreamArtist: Towards Controllable One-Shot Text-To-Image Generation via Contrastive Prompt-Tuning”, Dong et al 2022
- “DiffusionDet: Diffusion Model for Object Detection”, Chen et al 2022
- “Null-Text Inversion for Editing Real Images Using Guided Diffusion Models”, Mokady et al 2022
- “InstructPix2Pix: Learning to Follow Image Editing Instructions”, Brooks et al 2022
- “Versatile Diffusion: Text, Images and Variations All in One Diffusion Model”, Xu et al 2022
- “Rickrolling the Artist: Injecting Invisible Backdoors into Text-Guided Image Generation Models”, Struppek et al 2022
- “EDiff-I: Text-To-Image Diffusion Models With an Ensemble of Expert Denoisers”, Balaji et al 2022
- “DiffusionDB: A Large-Scale Prompt Gallery Dataset for Text-To-Image Generative Models”, Wang et al 2022
- “Imagic: Text-Based Real Image Editing With Diffusion Models”, Kawar et al 2022
- “Hierarchical Diffusion Models for Singing Voice Neural Vocoder”, Takahashi et al 2022
- “Flow Matching for Generative Modeling”, Lipman et al 2022
- “On Distillation of Guided Diffusion Models”, Meng et al 2022
- “Improving Sample Quality of Diffusion Models Using Self-Attention Guidance”, Hong et al 2022
- “Rectified Flow: A Marginal Preserving Approach to Optimal Transport”, Liu 2022
- “DreamFusion: Text-To-3D Using 2D Diffusion”, Poole et al 2022
- “RealSinger: Ultra-Realistic Singing Voice Generation via Stochastic Differential Equations”, Anonymous 2022
-
“
g.pt: Learning to Learn With Generative Models of Neural Network Checkpoints”, Peebles et al 2022 - “PFGM: Poisson Flow Generative Models”, Xu et al 2022
- “Brain Imaging Generation With Latent Diffusion Models”, Pinaya et al 2022
- “Soft Diffusion: Score Matching for General Corruptions”, Daras et al 2022
- “Flow Straight and Fast: Learning to Generate and Transfer Data With Rectified Flow”, Liu et al 2022
- “Frido: Feature Pyramid Diffusion for Complex Scene Image Synthesis”, Fan et al 2022
- “Understanding Diffusion Models: A Unified Perspective”, Luo 2022
- “DreamBooth: Fine Tuning Text-To-Image Diffusion Models for Subject-Driven Generation”, Ruiz et al 2022
- “Cold Diffusion: Inverting Arbitrary Image Transforms Without Noise”, Bansal et al 2022
- “Diffusion-QL: Diffusion Policies As an Expressive Policy Class for Offline Reinforcement Learning”, Wang et al 2022
- “An Image Is Worth One Word: Personalizing Text-To-Image Generation Using Textual Inversion”, Gal et al 2022
- “Prompt-To-Prompt Image Editing With Cross Attention Control”, Hertz et al 2022
- “Text-Guided Synthesis of Artistic Images With Retrieval-Augmented Diffusion Models”, Rombach et al 2022
- “NUWA-∞: Autoregressive over Autoregressive Generation for Infinite Visual Synthesis”, Wu et al 2022
- “IHDM: Generative Modelling With Inverse Heat Dissipation”, Rissanen et al 2022
- “DiffC: Lossy Compression With Gaussian Diffusion”, Theis et al 2022
- “Diffusion-GAN: Training GANs With Diffusion”, Wang et al 2022
- “Compositional Visual Generation With Composable Diffusion Models”, Liu et al 2022
- “DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps”, Lu et al 2022
- “Score-Based Generative Models Detect Manifolds”, Pidstrigach 2022
- “Elucidating the Design Space of Diffusion-Based Generative Models”, Karras et al 2022
- “Text2Human: Text-Driven Controllable Human Image Generation”, Jiang et al 2022
- “Improved Vector Quantized Diffusion Models”, Tang et al 2022
- “Maximum Likelihood Training of Implicit Nonlinear Diffusion Models”, Kim et al 2022
- “Imagen: Photorealistic Text-To-Image Diffusion Models With Deep Language Understanding”, Saharia et al 2022
- “Flexible Diffusion Modeling of Long Videos”, Harvey et al 2022
- “Planning With Diffusion for Flexible Behavior Synthesis”, Janner et al 2022
- “Diffusion Models for Adversarial Purification”, Nie et al 2022
- “Retrieval-Augmented Diffusion Models: Semi-Parametric Neural Image Synthesis”, Blattmann et al 2022
- “Video Diffusion Models”, Ho et al 2022
- “KNN-Diffusion: Image Generation via Large-Scale Retrieval”, Ashual et al 2022
- “Perception Prioritized Training of Diffusion Models”, Choi et al 2022
- “Diffusion Probabilistic Modeling for Video Generation”, Yang et al 2022
- “Diffusion Causal Models for Counterfactual Estimation”, Sanchez & Tsaftaris 2022
- “Truncated Diffusion Probabilistic Models and Diffusion-Based Adversarial Auto-Encoders”, Zheng et al 2022
- “Learning Fast Samplers for Diffusion Models by Differentiating Through Sample Quality”, Watson et al 2022
- “From Data to Functa: Your Data Point Is a Function and You Should Treat It like One”, Dupont et al 2022
- “Denoising Diffusion Restoration Models”, Kawar et al 2022
- “DiffuseVAE: Efficient, Controllable and High-Fidelity Generation from Low-Dimensional Latents”, Pandey et al 2022
- “Itô-Taylor Sampling Scheme for Denoising Diffusion Probabilistic Models Using Ideal Derivatives”, Tachibana et al 2021
- “High-Resolution Image Synthesis With Latent Diffusion Models”, Rombach et al 2021
- “High Fidelity Visualization of What Your Self-Supervised Representation Knows About”, Bordes et al 2021
- “More Control for Free! Image Synthesis With Semantic Diffusion Guidance”, Liu et al 2021
- “Come-Closer-Diffuse-Faster: Accelerating Conditional Diffusion Models for Inverse Problems through Stochastic Contraction”, Chung et al 2021
- “VQ-DDM: Global Context With Discrete Diffusion in Vector Quantized Modelling for Image Generation”, Hu et al 2021
- “Diffusion Autoencoders: Toward a Meaningful and Decodable Representation”, Preechakul et al 2021
- “Blended Diffusion for Text-Driven Editing of Natural Images”, Avrahami et al 2021
- “Vector Quantized Diffusion Model for Text-To-Image Synthesis”, Gu et al 2021
- “Classifier-Free Diffusion Guidance”, Ho & Salimans 2021
- “Unleashing Transformers: Parallel Token Prediction With Discrete Absorbing Diffusion for Fast High-Resolution Image Generation from Vector-Quantized Codes”, Bond-Taylor et al 2021
- “Restormer: Efficient Transformer for High-Resolution Image Restoration”, Zamir et al 2021
- “Tackling the Generative Learning Trilemma With Denoising Diffusion GANs”, Xiao et al 2021
- “Diffusion Normalizing Flow”, Zhang & Chen 2021
- “Palette: Image-To-Image Diffusion Models”, Saharia et al 2021
- “Progressive Distillation for Fast Sampling of Diffusion Models”, Salimans & Ho 2021
- “DiffusionCLIP: Text-Guided Image Manipulation Using Diffusion Models”, Kim & Ye 2021
- “Unconditional Diffusion Guidance”, Ho & Salimans 2021
- “Generative Probabilistic Image Colorization”, Furusawa et al 2021
- “Bilateral Denoising Diffusion Models”, Lam et al 2021
- “ImageBART: Bidirectional Context With Multinomial Diffusion for Autoregressive Image Synthesis”, Esser et al 2021
- “Variational Diffusion Models”, Kingma et al 2021
- “LoRA: Low-Rank Adaptation of Large Language Models”, Hu et al 2021
- “PriorGrad: Improving Conditional Denoising Diffusion Models With Data-Dependent Adaptive Prior”, Lee et al 2021
- “Score-Based Generative Modeling in Latent Space”, Vahdat et al 2021
- “CDM: Cascaded Diffusion Models for High Fidelity Image Generation”, Ho et al 2021
- “Learning to Efficiently Sample from Diffusion Probabilistic Models”, Watson et al 2021
- “Gotta Go Fast When Generating Data With Score-Based Models”, Jolicoeur-Martineau et al 2021
- “Diffusion Models Beat GANs on Image Synthesis”, Dhariwal & Nichol 2021
- “DiffSinger: Singing Voice Synthesis via Shallow Diffusion Mechanism”, Liu et al 2021
- “Image Super-Resolution via Iterative Refinement”, Saharia et al 2021
- “Learning Energy-Based Models by Diffusion Recovery Likelihood”, Gao et al 2021
- “Improved Denoising Diffusion Probabilistic Models”, Nichol & Dhariwal 2021
- “Denoising Diffusion Implicit Models”, Song et al 2021
- “Maximum Likelihood Training of Score-Based Diffusion Models”, Song et al 2021
- “Score-Based Generative Modeling through Stochastic Differential Equations”, Song et al 2020
- “Denoising Diffusion Probabilistic Models”, Ho et al 2020
- “NoGAN: Decrappification, DeOldification, and Super Resolution”, Antic et al 2019
- “Conceptual Captions: A Cleaned, Hypernymed, Image Alt-Text Dataset For Automatic Image Captioning”, Sharma et al 2018
- “Improving Sampling from Generative Autoencoders With Markov Chains”, Creswell et al 2016
- “Deep Unsupervised Learning Using Nonequilibrium Thermodynamics”, Sohl-Dickstein et al 2015
- “A Connection Between Score Matching and Denoising Autoencoders”, Vincent 2011
- “Optimal Approximation of Signal Priors”, Hyvarinen 2008
- “Estimation of Non-Normalized Statistical Models by Score Matching”, Hyvarinen 2005
- “Generative Modeling by Estimating Gradients of the Data Distribution”
- Sort By Magic
- Wikipedia
- Miscellaneous
- Link Bibliography
See Also
Gwern
“Research Ideas”, Gwern 2017
Links
“Long-Form Music Generation With Latent Diffusion”, Evans et al 2024
“VASA-1: Lifelike Audio-Driven Talking Faces Generated in Real Time”, Xu et al 2024
VASA-1: Lifelike Audio-Driven Talking Faces Generated in Real Time
“Measuring Style Similarity in Diffusion Models”, Somepalli et al 2024
“Is Model Collapse Inevitable? Breaking the Curse of Recursion by Accumulating Real and Synthetic Data”, Gerstgrasser et al 2024
“TextCraftor: Your Text Encoder Can Be Image Quality Controller”, Li et al 2024
TextCraftor: Your Text Encoder Can be Image Quality Controller
“Improving Text-To-Image Consistency via Automatic Prompt Optimization”, Mañas et al 2024
Improving Text-to-Image Consistency via Automatic Prompt Optimization
“SDXS: Real-Time One-Step Latent Diffusion Models With Image Conditions”, Song et al 2024
SDXS: Real-Time One-Step Latent Diffusion Models with Image Conditions
“CMD: Efficient Video Diffusion Models via Content-Frame Motion-Latent Decomposition”, Yu et al 2024
CMD: Efficient Video Diffusion Models via Content-Frame Motion-Latent Decomposition
“ZigMa: Zigzag Mamba Diffusion Model”, Hu et al 2024
“Atomically Accurate de Novo Design of Single-Domain Antibodies”, Bennett et al 2024
Atomically accurate de novo design of single-domain antibodies
“Sketch2Manga: Shaded Manga Screening from Sketch With Diffusion Models”, Lin et al 2024
Sketch2Manga: Shaded Manga Screening from Sketch with Diffusion Models
“ELLA: Equip Diffusion Models With LLM for Enhanced Semantic Alignment”, Hu et al 2024
ELLA: Equip Diffusion Models with LLM for Enhanced Semantic Alignment
“Transparent Image Layer Diffusion Using Latent Transparency”, Zhang & Agrawala 2024
“CartoonizeDiff: Diffusion-Based Photo Cartoonization Scheme”, Jeon et al 2024
“Discovering Universal Semantic Triggers for Text-To-Image Synthesis”, Zhai et al 2024
Discovering Universal Semantic Triggers for Text-to-Image Synthesis
“AnimeDiffusion: Anime Diffusion Colorization”, Cao et al 2024
“Why a Chinese Court’s Landmark Decision Recognising the Copyright for an AI-Generated Image Benefits Creators in This Nascent Field”, Shen 2024
“Bridging the Gap: Sketch to Color Diffusion Model With Semantic Prompt Learning”, Wang et al 2024
Bridging the Gap: Sketch to Color Diffusion Model with Semantic Prompt Learning
“GenCast: Diffusion-Based Ensemble Forecasting for Medium-Range Weather”, Price et al 2023
GenCast: Diffusion-based ensemble forecasting for medium-range weather
“Training Stable Diffusion from Scratch Costs <$160k”, Stephenson & Seguin 2023
“Generative AI Beyond LLMs: System Implications of Multi-Modal Generation”, Golden et al 2023
Generative AI Beyond LLMs: System Implications of Multi-Modal Generation
“DreamTuner: Single Image Is Enough for Subject-Driven Generation”, Hua et al 2023
DreamTuner: Single Image is Enough for Subject-Driven Generation
“Rich Human Feedback for Text-To-Image Generation”, Liang et al 2023
“ECLIPSE: A Resource-Efficient Text-To-Image Prior for Image Generations”, Patel et al 2023
ECLIPSE: A Resource-Efficient Text-to-Image Prior for Image Generations
“Self-Conditioned Image Generation via Generating Representations”, Li et al 2023
Self-conditioned Image Generation via Generating Representations
“Retrieving Conditions from Reference Images for Diffusion Models”, Tang et al 2023
Retrieving Conditions from Reference Images for Diffusion Models
“Analyzing and Improving the Training Dynamics of Diffusion Models”, Karras et al 2023
Analyzing and Improving the Training Dynamics of Diffusion Models
“DiffiT: Diffusion Vision Transformers for Image Generation”, Hatamizadeh et al 2023
“Diffusion Models Without Attention”, Yan et al 2023
“MicroCinema: A Divide-And-Conquer Approach for Text-To-Video Generation”, Wang et al 2023
MicroCinema: A Divide-and-Conquer Approach for Text-to-Video Generation
“AnyLens: A Generative Diffusion Model With Any Rendering Lens”, Voynov et al 2023
AnyLens: A Generative Diffusion Model with Any Rendering Lens
“TextDiffuser-2: Unleashing the Power of Language Models for Text Rendering”, Chen et al 2023
TextDiffuser-2: Unleashing the Power of Language Models for Text Rendering
“MobileDiffusion: Subsecond Text-To-Image Generation on Mobile Devices”, Zhao et al 2023
MobileDiffusion: Subsecond Text-to-Image Generation on Mobile Devices
“Adversarial Diffusion Distillation”, Sauer et al 2023
“Generative Models: What Do They Know? Do They Know Things? Let’s Find Out!”, Du et al 2023
Generative Models: What do they know? Do they know things? Let’s find out!
“Test-Time Adaptation of Discriminative Models via Diffusion Generative Feedback”, Prabhudesai et al 2023
Test-time Adaptation of Discriminative Models via Diffusion Generative Feedback
“Diffusion Model Alignment Using Direct Preference Optimization”, Wallace et al 2023
Diffusion Model Alignment Using Direct Preference Optimization
“Concept Sliders: LoRA Adaptors for Precise Control in Diffusion Models”, Gandikota et al 2023
Concept Sliders: LoRA Adaptors for Precise Control in Diffusion Models
“UFOGen: You Forward Once Large Scale Text-To-Image Generation via Diffusion GANs”, Xu et al 2023
UFOGen: You Forward Once Large Scale Text-to-Image Generation via Diffusion GANs
“I2VGen-XL: High-Quality Image-To-Video Synthesis via Cascaded Diffusion Models”, Zhang et al 2023
I2VGen-XL: High-Quality Image-to-Video Synthesis via Cascaded Diffusion Models
“AnyText: Multilingual Visual Text Generation And Editing”, Tuo et al 2023
“Idempotent Generative Network”, Shocher et al 2023
“Beyond U: Making Diffusion Models Faster & Lighter”, Calvo-Ordonez et al 2023
“CADS: Unleashing the Diversity of Diffusion Models through Condition-Annealed Sampling”, Sadat et al 2023
CADS: Unleashing the Diversity of Diffusion Models through Condition-Annealed Sampling
“CommonCanvas: An Open Diffusion Model Trained With Creative-Commons Images”, Gokaslan et al 2023
CommonCanvas: An Open Diffusion Model Trained with Creative-Commons Images
“Prompt-Specific Poisoning Attacks on Text-To-Image Generative Models”, Shan et al 2023
Prompt-Specific Poisoning Attacks on Text-to-Image Generative Models
“Generalization in Diffusion Models Arises from Geometry-Adaptive Harmonic Representation”, Kadkhodaie et al 2023
Generalization in diffusion models arises from geometry-adaptive harmonic representation
“Emu: Enhancing Image Generation Models Using Photogenic Needles in a Haystack”, Dai et al 2023
Emu: Enhancing Image Generation Models Using Photogenic Needles in a Haystack
“Generating and Imputing Tabular Data via Diffusion and Flow-Based Gradient-Boosted Trees”, Jolicoeur-Martineau et al 2023
Generating and Imputing Tabular Data via Diffusion and Flow-based Gradient-Boosted Trees
“InstaFlow: One Step Is Enough for High-Quality Diffusion-Based Text-To-Image Generation”, Liu et al 2023
InstaFlow: One Step is Enough for High-Quality Diffusion-Based Text-to-Image Generation
“MetaDiff: Meta-Learning With Conditional Diffusion for Few-Shot Learning”, Zhang & Yu 2023
MetaDiff: Meta-Learning with Conditional Diffusion for Few-Shot Learning
“Provable Guarantees for Generative Behavior Cloning: Bridging Low-Level Stability and High-Level Behavior”, Block et al 2023
“Diffusion Models Beat GANs on Image Classification”, Mukhopadhyay et al 2023
“SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis”, Podell et al 2023
SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis
“SDXL § Micro-Conditioning: Conditioning the Model on Image Size”, Podell et al 2023 (page 3 org stability)
SDXL § Micro-Conditioning: Conditioning the Model on Image Size
“DiffSketcher: Text Guided Vector Sketch Synthesis through Latent Diffusion Models”, Xing et al 2023
DiffSketcher: Text Guided Vector Sketch Synthesis through Latent Diffusion Models
“Semi-Implicit Denoising Diffusion Models (SIDDMs)”, Xu et al 2023
“StyleTTS 2: Towards Human-Level Text-To-Speech through Style Diffusion and Adversarial Training With Large Speech Language Models”, Li et al 2023
“Beyond Surface Statistics: Scene Representations in a Latent Diffusion Model”, Chen et al 2023
Beyond Surface Statistics: Scene Representations in a Latent Diffusion Model
“Exposing Flaws of Generative Model Evaluation Metrics and Their Unfair Treatment of Diffusion Models”, Stein et al 2023
Exposing flaws of generative model evaluation metrics and their unfair treatment of diffusion models
“StyleDrop: Text-To-Image Generation in Any Style”, Sohn et al 2023
“Artificial Intelligence and Art: Identifying the Esthetic Judgment Factors That Distinguish Human & Machine-Generated Artwork”, Samo & Highhouse 2023
“Spontaneous Symmetry Breaking in Generative Diffusion Models”, Raya & Ambrogioni 2023
Spontaneous symmetry breaking in generative diffusion models
“Tree-Ring Watermarks: Fingerprints for Diffusion Images That Are Invisible and Robust”, Wen et al 2023
Tree-Ring Watermarks: Fingerprints for Diffusion Images that are Invisible and Robust
“Generalizable Synthetic Image Detection via Language-Guided Contrastive Learning”, Wu et al 2023
Generalizable Synthetic Image Detection via Language-guided Contrastive Learning
“Common Diffusion Noise Schedules and Sample Steps Are Flawed”, Lin et al 2023
Common Diffusion Noise Schedules and Sample Steps are Flawed
“Diffusart: Enhancing Line Art Colorization With Conditional Diffusion Models”, Carrillo et al 2023
Diffusart: Enhancing Line Art Colorization with Conditional Diffusion Models
“Continual Diffusion: Continual Customization of Text-To-Image Diffusion With C-LoRA”, Smith et al 2023
Continual Diffusion: Continual Customization of Text-to-Image Diffusion with C-LoRA
“Reference-Based Image Composition With Sketch via Structure-Aware Diffusion Model”, Kim et al 2023
Reference-based Image Composition with Sketch via Structure-aware Diffusion Model
“Masked Diffusion Transformer Is a Strong Image Synthesizer”, Gao et al 2023
“Prompting AI Art: An Investigation into the Creative Skill of Prompt Engineering”, Oppenlaender et al 2023
Prompting AI Art: An Investigation into the Creative Skill of Prompt Engineering
“TRACT: Denoising Diffusion Models With Transitive Closure Time-Distillation”, Berthelot et al 2023
TRACT: Denoising Diffusion Models with Transitive Closure Time-Distillation
“Consistency Models”, Song et al 2023
“Understanding the Diffusion Objective As a Weighted Integral of ELBOs”, Kingma & Gao 2023
Understanding the Diffusion Objective as a Weighted Integral of ELBOs
“Adding Conditional Control to Text-To-Image Diffusion Models”, Zhang et al 2023
Adding Conditional Control to Text-to-Image Diffusion Models
“Glaze: Protecting Artists from Style Mimicry by Text-To-Image Models”, Shan et al 2023
Glaze: Protecting Artists from Style Mimicry by Text-to-Image Models
“Hard Prompts Made Easy: Gradient-Based Discrete Optimization for Prompt Tuning and Discovery”, Wen et al 2023
Hard Prompts Made Easy: Gradient-Based Discrete Optimization for Prompt Tuning and Discovery
“Dreamix: Video Diffusion Models Are General Video Editors”, Molad et al 2023
“Imitating Human Behavior With Diffusion Models”, Pearce et al 2023
“Msanii: High Fidelity Music Synthesis on a Shoestring Budget”, Maina 2023
Msanii: High Fidelity Music Synthesis on a Shoestring Budget
“Archisound: Audio Generation With Diffusion”, Schneider 2023
“DIRAC: Neural Image Compression With a Diffusion-Based Decoder”, Goose et al 2023
DIRAC: Neural Image Compression with a Diffusion-Based Decoder
“Tune-A-Video: One-Shot Tuning of Image Diffusion Models for Text-To-Video Generation”, Wu et al 2022
Tune-A-Video: One-Shot Tuning of Image Diffusion Models for Text-to-Video Generation
“Character-Aware Models Improve Visual Text Rendering”, Liu et al 2022
“Diffusion Transformers (DiTs): Scalable Diffusion Models With Transformers”, Peebles & Xie 2022
Diffusion Transformers (DiTs): Scalable Diffusion Models with Transformers
“Point·E: A System for Generating 3D Point Clouds from Complex Prompts”, Nichol et al 2022
Point·E: A System for Generating 3D Point Clouds from Complex Prompts
“The Stable Artist: Steering Semantics in Diffusion Latent Space”, Brack et al 2022
The Stable Artist: Steering Semantics in Diffusion Latent Space
“Multi-Concept Customization of Text-To-Image Diffusion”, Kumari et al 2022
“Multi-Resolution Textual Inversion”, Daras & Dimakis 2022
“Latent Video Diffusion Models for High-Fidelity Video Generation With Arbitrary Lengths”, He et al 2022
Latent Video Diffusion Models for High-Fidelity Video Generation with Arbitrary Lengths
“VectorFusion: Text-To-SVG by Abstracting Pixel-Based Diffusion Models”, Jain et al 2022
VectorFusion: Text-to-SVG by Abstracting Pixel-Based Diffusion Models
“DreamArtist: Towards Controllable One-Shot Text-To-Image Generation via Contrastive Prompt-Tuning”, Dong et al 2022
DreamArtist: Towards Controllable One-Shot Text-to-Image Generation via Contrastive Prompt-Tuning
“DiffusionDet: Diffusion Model for Object Detection”, Chen et al 2022
“Null-Text Inversion for Editing Real Images Using Guided Diffusion Models”, Mokady et al 2022
Null-text Inversion for Editing Real Images using Guided Diffusion Models
“InstructPix2Pix: Learning to Follow Image Editing Instructions”, Brooks et al 2022
InstructPix2Pix: Learning to Follow Image Editing Instructions
“Versatile Diffusion: Text, Images and Variations All in One Diffusion Model”, Xu et al 2022
Versatile Diffusion: Text, Images and Variations All in One Diffusion Model
“Rickrolling the Artist: Injecting Invisible Backdoors into Text-Guided Image Generation Models”, Struppek et al 2022
Rickrolling the Artist: Injecting Invisible Backdoors into Text-Guided Image Generation Models
“EDiff-I: Text-To-Image Diffusion Models With an Ensemble of Expert Denoisers”, Balaji et al 2022
eDiff-I: Text-to-Image Diffusion Models with an Ensemble of Expert Denoisers
“DiffusionDB: A Large-Scale Prompt Gallery Dataset for Text-To-Image Generative Models”, Wang et al 2022
DiffusionDB: A Large-scale Prompt Gallery Dataset for Text-to-Image Generative Models
“Imagic: Text-Based Real Image Editing With Diffusion Models”, Kawar et al 2022
“Hierarchical Diffusion Models for Singing Voice Neural Vocoder”, Takahashi et al 2022
Hierarchical Diffusion Models for Singing Voice Neural Vocoder
“Flow Matching for Generative Modeling”, Lipman et al 2022
“On Distillation of Guided Diffusion Models”, Meng et al 2022
“Improving Sample Quality of Diffusion Models Using Self-Attention Guidance”, Hong et al 2022
Improving Sample Quality of Diffusion Models Using Self-Attention Guidance
“Rectified Flow: A Marginal Preserving Approach to Optimal Transport”, Liu 2022
Rectified Flow: A Marginal Preserving Approach to Optimal Transport
“DreamFusion: Text-To-3D Using 2D Diffusion”, Poole et al 2022
“RealSinger: Ultra-Realistic Singing Voice Generation via Stochastic Differential Equations”, Anonymous 2022
RealSinger: Ultra-Realistic Singing Voice Generation via Stochastic Differential Equations
“g.pt: Learning to Learn With Generative Models of Neural Network Checkpoints”, Peebles et al 2022
g.pt: Learning to Learn with Generative Models of Neural Network Checkpoints
“PFGM: Poisson Flow Generative Models”, Xu et al 2022
“Brain Imaging Generation With Latent Diffusion Models”, Pinaya et al 2022
“Soft Diffusion: Score Matching for General Corruptions”, Daras et al 2022
“Flow Straight and Fast: Learning to Generate and Transfer Data With Rectified Flow”, Liu et al 2022
Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow
“Frido: Feature Pyramid Diffusion for Complex Scene Image Synthesis”, Fan et al 2022
Frido: Feature Pyramid Diffusion for Complex Scene Image Synthesis
“Understanding Diffusion Models: A Unified Perspective”, Luo 2022
“DreamBooth: Fine Tuning Text-To-Image Diffusion Models for Subject-Driven Generation”, Ruiz et al 2022
DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation
“Cold Diffusion: Inverting Arbitrary Image Transforms Without Noise”, Bansal et al 2022
Cold Diffusion: Inverting Arbitrary Image Transforms Without Noise
“Diffusion-QL: Diffusion Policies As an Expressive Policy Class for Offline Reinforcement Learning”, Wang et al 2022
Diffusion-QL: Diffusion Policies as an Expressive Policy Class for Offline Reinforcement Learning
“An Image Is Worth One Word: Personalizing Text-To-Image Generation Using Textual Inversion”, Gal et al 2022
An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion
“Prompt-To-Prompt Image Editing With Cross Attention Control”, Hertz et al 2022
“Text-Guided Synthesis of Artistic Images With Retrieval-Augmented Diffusion Models”, Rombach et al 2022
Text-Guided Synthesis of Artistic Images with Retrieval-Augmented Diffusion Models
“NUWA-∞: Autoregressive over Autoregressive Generation for Infinite Visual Synthesis”, Wu et al 2022
NUWA-∞: Autoregressive over Autoregressive Generation for Infinite Visual Synthesis
“IHDM: Generative Modelling With Inverse Heat Dissipation”, Rissanen et al 2022
“DiffC: Lossy Compression With Gaussian Diffusion”, Theis et al 2022
“Diffusion-GAN: Training GANs With Diffusion”, Wang et al 2022
“Compositional Visual Generation With Composable Diffusion Models”, Liu et al 2022
Compositional Visual Generation with Composable Diffusion Models
“DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps”, Lu et al 2022
DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps
“Score-Based Generative Models Detect Manifolds”, Pidstrigach 2022
“Elucidating the Design Space of Diffusion-Based Generative Models”, Karras et al 2022
Elucidating the Design Space of Diffusion-Based Generative Models
“Text2Human: Text-Driven Controllable Human Image Generation”, Jiang et al 2022
“Improved Vector Quantized Diffusion Models”, Tang et al 2022
“Maximum Likelihood Training of Implicit Nonlinear Diffusion Models”, Kim et al 2022
Maximum Likelihood Training of Implicit Nonlinear Diffusion Models
“Imagen: Photorealistic Text-To-Image Diffusion Models With Deep Language Understanding”, Saharia et al 2022
Imagen: Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding
“Flexible Diffusion Modeling of Long Videos”, Harvey et al 2022
“Planning With Diffusion for Flexible Behavior Synthesis”, Janner et al 2022
“Diffusion Models for Adversarial Purification”, Nie et al 2022
“Retrieval-Augmented Diffusion Models: Semi-Parametric Neural Image Synthesis”, Blattmann et al 2022
Retrieval-Augmented Diffusion Models: Semi-Parametric Neural Image Synthesis
“Video Diffusion Models”, Ho et al 2022
“KNN-Diffusion: Image Generation via Large-Scale Retrieval”, Ashual et al 2022
“Perception Prioritized Training of Diffusion Models”, Choi et al 2022
“Diffusion Probabilistic Modeling for Video Generation”, Yang et al 2022
“Diffusion Causal Models for Counterfactual Estimation”, Sanchez & Tsaftaris 2022
“Truncated Diffusion Probabilistic Models and Diffusion-Based Adversarial Auto-Encoders”, Zheng et al 2022
Truncated Diffusion Probabilistic Models and Diffusion-based Adversarial Auto-Encoders
“Learning Fast Samplers for Diffusion Models by Differentiating Through Sample Quality”, Watson et al 2022
Learning Fast Samplers for Diffusion Models by Differentiating Through Sample Quality
“From Data to Functa: Your Data Point Is a Function and You Should Treat It like One”, Dupont et al 2022
From data to functa: Your data point is a function and you should treat it like one
“Denoising Diffusion Restoration Models”, Kawar et al 2022
“DiffuseVAE: Efficient, Controllable and High-Fidelity Generation from Low-Dimensional Latents”, Pandey et al 2022
DiffuseVAE: Efficient, Controllable and High-Fidelity Generation from Low-Dimensional Latents
“Itô-Taylor Sampling Scheme for Denoising Diffusion Probabilistic Models Using Ideal Derivatives”, Tachibana et al 2021
Itô-Taylor Sampling Scheme for Denoising Diffusion Probabilistic Models using Ideal Derivatives
“High-Resolution Image Synthesis With Latent Diffusion Models”, Rombach et al 2021
High-Resolution Image Synthesis with Latent Diffusion Models
“High Fidelity Visualization of What Your Self-Supervised Representation Knows About”, Bordes et al 2021
High Fidelity Visualization of What Your Self-Supervised Representation Knows About
“More Control for Free! Image Synthesis With Semantic Diffusion Guidance”, Liu et al 2021
More Control for Free! Image Synthesis with Semantic Diffusion Guidance
“Come-Closer-Diffuse-Faster: Accelerating Conditional Diffusion Models for Inverse Problems through Stochastic Contraction”, Chung et al 2021
“VQ-DDM: Global Context With Discrete Diffusion in Vector Quantized Modelling for Image Generation”, Hu et al 2021
VQ-DDM: Global Context with Discrete Diffusion in Vector Quantized Modelling for Image Generation
“Diffusion Autoencoders: Toward a Meaningful and Decodable Representation”, Preechakul et al 2021
Diffusion Autoencoders: Toward a Meaningful and Decodable Representation
“Blended Diffusion for Text-Driven Editing of Natural Images”, Avrahami et al 2021
“Vector Quantized Diffusion Model for Text-To-Image Synthesis”, Gu et al 2021
Vector Quantized Diffusion Model for Text-to-Image Synthesis
“Classifier-Free Diffusion Guidance”, Ho & Salimans 2021
“Unleashing Transformers: Parallel Token Prediction With Discrete Absorbing Diffusion for Fast High-Resolution Image Generation from Vector-Quantized Codes”, Bond-Taylor et al 2021
“Restormer: Efficient Transformer for High-Resolution Image Restoration”, Zamir et al 2021
Restormer: Efficient Transformer for High-Resolution Image Restoration
“Tackling the Generative Learning Trilemma With Denoising Diffusion GANs”, Xiao et al 2021
Tackling the Generative Learning Trilemma with Denoising Diffusion GANs
“Diffusion Normalizing Flow”, Zhang & Chen 2021
“Palette: Image-To-Image Diffusion Models”, Saharia et al 2021
“Progressive Distillation for Fast Sampling of Diffusion Models”, Salimans & Ho 2021
Progressive Distillation for Fast Sampling of Diffusion Models
“DiffusionCLIP: Text-Guided Image Manipulation Using Diffusion Models”, Kim & Ye 2021
DiffusionCLIP: Text-guided Image Manipulation Using Diffusion Models
“Unconditional Diffusion Guidance”, Ho & Salimans 2021
“Generative Probabilistic Image Colorization”, Furusawa et al 2021
“Bilateral Denoising Diffusion Models”, Lam et al 2021
“ImageBART: Bidirectional Context With Multinomial Diffusion for Autoregressive Image Synthesis”, Esser et al 2021
ImageBART: Bidirectional Context with Multinomial Diffusion for Autoregressive Image Synthesis
“Variational Diffusion Models”, Kingma et al 2021
“LoRA: Low-Rank Adaptation of Large Language Models”, Hu et al 2021
“PriorGrad: Improving Conditional Denoising Diffusion Models With Data-Dependent Adaptive Prior”, Lee et al 2021
PriorGrad: Improving Conditional Denoising Diffusion Models with Data-Dependent Adaptive Prior
“Score-Based Generative Modeling in Latent Space”, Vahdat et al 2021
“CDM: Cascaded Diffusion Models for High Fidelity Image Generation”, Ho et al 2021
CDM: Cascaded Diffusion Models for High Fidelity Image Generation
“Learning to Efficiently Sample from Diffusion Probabilistic Models”, Watson et al 2021
Learning to Efficiently Sample from Diffusion Probabilistic Models
“Gotta Go Fast When Generating Data With Score-Based Models”, Jolicoeur-Martineau et al 2021
“Diffusion Models Beat GANs on Image Synthesis”, Dhariwal & Nichol 2021
“DiffSinger: Singing Voice Synthesis via Shallow Diffusion Mechanism”, Liu et al 2021
DiffSinger: Singing Voice Synthesis via Shallow Diffusion Mechanism
“Image Super-Resolution via Iterative Refinement”, Saharia et al 2021
“Learning Energy-Based Models by Diffusion Recovery Likelihood”, Gao et al 2021
Learning Energy-Based Models by Diffusion Recovery Likelihood
“Improved Denoising Diffusion Probabilistic Models”, Nichol & Dhariwal 2021
“Denoising Diffusion Implicit Models”, Song et al 2021
“Maximum Likelihood Training of Score-Based Diffusion Models”, Song et al 2021
“Score-Based Generative Modeling through Stochastic Differential Equations”, Song et al 2020
Score-Based Generative Modeling through Stochastic Differential Equations
“Denoising Diffusion Probabilistic Models”, Ho et al 2020
“NoGAN: Decrappification, DeOldification, and Super Resolution”, Antic et al 2019
NoGAN: Decrappification, DeOldification, and Super Resolution
“Improving Sampling from Generative Autoencoders With Markov Chains”, Creswell et al 2016
Improving Sampling from Generative Autoencoders with Markov Chains
“Deep Unsupervised Learning Using Nonequilibrium Thermodynamics”, Sohl-Dickstein et al 2015
Deep Unsupervised Learning using Nonequilibrium Thermodynamics
“A Connection Between Score Matching and Denoising Autoencoders”, Vincent 2011
A Connection Between Score Matching and Denoising Autoencoders
“Optimal Approximation of Signal Priors”, Hyvarinen 2008
“Estimation of Non-Normalized Statistical Models by Score Matching”, Hyvarinen 2005
Estimation of Non-Normalized Statistical Models by Score Matching
“Generative Modeling by Estimating Gradients of the Data Distribution”
Generative Modeling by Estimating Gradients of the Data Distribution
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diffusion-modeling
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Miscellaneous
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/doc/ai/nn/diffusion/2023-podell-figure2-datalossduetononsquareimageaspectratios.png: -
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/doc/ai/nn/diffusion/2021-nichol-figure10-scalinglawsforddpmincomputevsnllfid.png: -
https://blog.metaphysic.ai/the-road-to-realistic-full-body-deepfakes/ -
https://blog.novelai.net/novelai-improvements-on-stable-diffusion-e10d38db82ac -
https://blog.research.google/2023/01/google-research-2022-beyond-language.html -
https://blog.research.google/2024/01/mobilediffusion-rapid-text-to-image.html -
https://bonfx.com/how-to-use-dreamstudio-stablediffusion-to-create-a-traditional-illustration/: -
https://colab.research.google.com/drive/1dlgggNa5Mz8sEAGU0wFCHhGLFooW_pf1 -
https://discuss.huggingface.co/t/decoding-latents-to-rgb-without-upscaling/23204/4 -
https://docs.google.com/spreadsheets/d/14xTqtuV3BuKDNhLotB_d1aFlBGnDJOY0BRXJ8-86GpA/edit: -
https://drive.google.com/drive/folders/1wXvivH2azyK0J-5kjxiq5_4BlMw0ztmx -
https://fortune.com/2023/11/29/stability-ai-sale-intel-ceo-resign/ -
https://generalrobots.substack.com/p/dimension-hopper-part-1 -
https://github.com/curiousjp/toy_sd_genetics?tab=readme-ov-file#toy_sd_genetics -
https://github.com/marqo-ai/marqo/blob/mainline/examples/StableDiffusion/hot-dog-100k.md: -
https://github.com/openai/guided-diffusion#download-pre-trained-models -
https://github.com/vitoplantamura/OnnxStream/tree/846da873570a737b49154e8f835704264864b0fe -
https://globalcomix.com/c/paintings-photographs/chapters/en/1/1 -
https://hforsten.com/identifying-stable-diffusion-xl-10-images-from-vae-artifacts.html -
https://huggingface.co/Gustavosta/MagicPrompt-Stable-Diffusion -
https://huggingface.co/Onodofthenorth/SD_PixelArt_SpriteSheet_Generator -
https://huggingface.co/Ryukijano/CatCon-Controlnet-WD-1-5-b2R -
https://jxmo.notion.site/The-Weird-and-Wonderful-World-of-AI-Art-b9615a2e7278435b98380ff81ae1cf09 -
https://keras.io/examples/generative/random_walks_with_stable_diffusion/:View External Link:
https://keras.io/examples/generative/random_walks_with_stable_diffusion/ -
https://lambdalabs.com/blog/inference-benchmark-stable-diffusion:View HTML (22MB):
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https://lxj616.github.io/jekyll/update/2022/05/14/rethinking-the-danbooru-2021-dataset.html -
https://medium.com/@enryu9000/anifusion-diffusion-models-for-anime-pictures-138cf1af2cbe -
https://minimaxir.com/2022/11/stable-diffusion-negative-prompt/:View External Link:
https://minimaxir.com/2022/11/stable-diffusion-negative-prompt/ -
https://nostalgebraist.tumblr.com/post/672300992964050944/franks-image-generation-model-explained: -
https://old.reddit.com/r/StableDiffusion/comments/y91pp7/stable_diffusion_v15/: -
https://paperswithcode.com/sota/text-to-image-generation-on-coco -
https://plai.cs.ubc.ca/2022/05/20/flexible-diffusion-modeling-of-long-videos/ -
https://pub.towardsai.net/stable-diffusion-based-image-compresssion-6f1f0a399202 -
https://saltacc.notion.site/saltacc/WD-1-5-Beta-3-Release-Notes-1e35a0ed1bb24c5b93ec79c45c217f63 -
https://talesofsyn.com/posts/creating-isometric-rpg-game-backgrounds -
https://twitter.com/BjoernKarmann/status/1663496103998750721: -
https://twitter.com/Omorfiamorphism/status/1564633854119477257 -
https://twitter.com/SimonGColton/status/1578162486712287233: -
https://twitter.com/jasonbaldridge/status/1588017062802329604: -
https://twitter.com/novelaiofficial/status/1723601550927356343 -
https://twitter.com/pascalblanche/status/1552698745485246471 -
https://twitter.com/pharmapsychotic/status/1577465085575909376: -
https://www.facebook.com/marcello.herreshoff/posts/10160262954262798 -
https://www.hollywoodreporter.com/tv/tv-news/secret-invasion-ai-opening-1235521299/: -
https://www.reddit.com/r/Bard/comments/1795exq/google_sge_image_generation_is_so_good_at/ -
https://www.reddit.com/r/StableDiffusion/comments/11f4zgt/remixing_memes_with_multi_controlnet_is/ -
https://www.reddit.com/r/StableDiffusion/comments/15aapcb/sdxl_10_is_out/: -
https://www.reddit.com/r/StableDiffusion/comments/18r7mqf/top_online_nsfw_creators_updated/ -
https://www.reddit.com/r/StableDiffusion/comments/1bsi2xs/the_experiment/ -
https://www.reddit.com/r/StableDiffusion/comments/ys434h/animating_generated_face_test/ -
https://www.reddit.com/r/StableDiffusion/comments/z0xyk2/dreambooth_model_for_cutting_machines/ -
https://www.reddit.com/r/aigamedev/comments/142j3yt/valve_is_not_willing_to_publish_games_with_ai/ -
https://www.reddit.com/r/sdnsfw/comments/ylo4eh/huge_list_of_sexy_tested_photorealism_keywords/: -
https://www.samdickie.me/writing/experiment-1-creating-a-landing-page-using-ai-tools-no-code -
https://www.stavros.io/posts/compressing-images-with-stable-diffusion/
Link Bibliography
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https://arxiv.org/abs/2403.13802: “ZigMa: Zigzag Mamba Diffusion Model”, Vincent Tao Hu, Stefan Andreas Baumann, Ming Gui, Olga Grebenkova, Pingchuan Ma, Johannes Fischer, Bjorn Ommer -
https://arxiv.org/abs/2312.02139: “DiffiT: Diffusion Vision Transformers for Image Generation”, Ali Hatamizadeh, Jiaming Song, Guilin Liu, Jan Kautz, Arash Vahdat -
https://arxiv.org/abs/2311.18829#microsoft: “MicroCinema: A Divide-And-Conquer Approach for Text-To-Video Generation”, -
https://arxiv.org/abs/2311.16465: “TextDiffuser-2: Unleashing the Power of Language Models for Text Rendering”, Jingye Chen, Yupan Huang, Tengchao Lv, Lei Cui, Qifeng Chen, Furu Wei -
https://arxiv.org/abs/2311.12092: “Concept Sliders: LoRA Adaptors for Precise Control in Diffusion Models”, Rohit Gandikota, Joanna Materzynska, Tingrui Zhou, Antonio Torralba, David Bau -
https://arxiv.org/abs/2311.09257#google: “UFOGen: You Forward Once Large Scale Text-To-Image Generation via Diffusion GANs”, Yanwu Xu, Yang Zhao, Zhisheng Xiao, Tingbo Hou -
https://arxiv.org/abs/2311.04145#alibaba: “I2VGen-XL: High-Quality Image-To-Video Synthesis via Cascaded Diffusion Models”, Shiwei Zhang, Jiayu Wang, Yingya Zhang, Kang Zhao, Hangjie Yuan, Zhiwu Qin, Xiang Wang, Deli Zhao, Jingren Zhou -
https://arxiv.org/abs/2310.16825: “CommonCanvas: An Open Diffusion Model Trained With Creative-Commons Images”, -
https://arxiv.org/abs/2309.15807#facebook: “Emu: Enhancing Image Generation Models Using Photogenic Needles in a Haystack”, -
https://arxiv.org/abs/2309.06380: “InstaFlow: One Step Is Enough for High-Quality Diffusion-Based Text-To-Image Generation”, Xingchao Liu, Xiwen Zhang, Jianzhu Ma, Jian Peng, Qiang Liu -
https://arxiv.org/abs/2307.01952#stability: “SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis”, Dustin Podell, Zion English, Kyle Lacey, Andreas Blattmann, Tim Dockhorn, Jonas Müller, Joe Penna, Robin Rombach -
https://arxiv.org/pdf/2307.01952.pdf#page=3&org=stability: “SDXL § Micro-Conditioning: Conditioning the Model on Image Size”, Dustin Podell, Zion English, Kyle Lacey, Andreas Blattmann, Tim Dockhorn, Jonas Müller, Joe Penna, Robin Rombach -
https://arxiv.org/abs/2306.07691: “StyleTTS 2: Towards Human-Level Text-To-Speech through Style Diffusion and Adversarial Training With Large Speech Language Models”, Yinghao Aaron Li, Cong Han, Vinay S. Raghavan, Gavin Mischler, Nima Mesgarani -
2023-samo.pdf: “Artificial Intelligence and Art: Identifying the Esthetic Judgment Factors That Distinguish Human & Machine-Generated Artwork”, Andrew Samo, Scott Highhouse -
https://arxiv.org/abs/2303.14389: “Masked Diffusion Transformer Is a Strong Image Synthesizer”, Shanghua Gao, Pan Zhou, Ming-Ming Cheng, Shuicheng Yan -
https://arxiv.org/abs/2303.01469#openai: “Consistency Models”, Yang Song, Prafulla Dhariwal, Mark Chen, Ilya Sutskever -
https://arxiv.org/abs/2302.04222: “Glaze: Protecting Artists from Style Mimicry by Text-To-Image Models”, Shawn Shan, Jenna Cryan, Emily Wenger, Haitao Zheng, Rana Hanocka, Ben Y. Zhao -
https://arxiv.org/abs/2302.01329#google: “Dreamix: Video Diffusion Models Are General Video Editors”, -
https://raw.githubusercontent.com/flavioschneider/master-thesis/main/audio_diffusion_thesis.pdf: “Archisound: Audio Generation With Diffusion”, Flavio Schneider -
https://arxiv.org/abs/2212.10562#google: “Character-Aware Models Improve Visual Text Rendering”, -
https://arxiv.org/abs/2212.08751#openai: “Point·E: A System for Generating 3D Point Clouds from Complex Prompts”, Alex Nichol, Heewoo Jun, Prafulla Dhariwal, Pamela Mishkin, Mark Chen -
https://arxiv.org/abs/2211.09788: “DiffusionDet: Diffusion Model for Object Detection”, Shoufa Chen, Peize Sun, Yibing Song, Ping Luo -
https://arxiv.org/abs/2211.09800: “InstructPix2Pix: Learning to Follow Image Editing Instructions”, Tim Brooks, Aleksander Holynski, Alexei A. Efros -
https://arxiv.org/abs/2211.01324#nvidia: “EDiff-I: Text-To-Image Diffusion Models With an Ensemble of Expert Denoisers”, -
https://arxiv.org/abs/2210.07508#sony: “Hierarchical Diffusion Models for Singing Voice Neural Vocoder”, Naoya Takahashi, Mayank Kumar, Singh, Yuki Mitsufuji -
https://arxiv.org/abs/2210.03142#google: “On Distillation of Guided Diffusion Models”, Chenlin Meng, Ruiqi Gao, Diederik P. Kingma, Stefano Ermon, Jonathan Ho, Tim Salimans -
https://arxiv.org/abs/2209.12892: “g.pt: Learning to Learn With Generative Models of Neural Network Checkpoints”, William Peebles, Ilija Radosavovic, Tim Brooks, Alexei A. Efros, Jitendra Malik -
https://arxiv.org/abs/2208.12242#google: “DreamBooth: Fine Tuning Text-To-Image Diffusion Models for Subject-Driven Generation”, Nataniel Ruiz, Yuanzhen Li, Varun Jampani, Yael Pritch, Michael Rubinstein, Kfir Aberman -
https://arxiv.org/abs/2208.01618: “An Image Is Worth One Word: Personalizing Text-To-Image Generation Using Textual Inversion”, Rinon Gal, Yuval Alaluf, Yuval Atzmon, Or Patashnik, Amit H. Bermano, Gal Chechik, Daniel Cohen-Or -
https://arxiv.org/abs/2207.09814#microsoft: “NUWA-∞: Autoregressive over Autoregressive Generation for Infinite Visual Synthesis”, Chenfei Wu, Jian Liang, Xiaowei Hu, Zhe Gan, Jianfeng Wang, Lijuan Wang, Zicheng Liu, Yuejian Fang, Nan Duan -
https://arxiv.org/abs/2205.16007#microsoft: “Improved Vector Quantized Diffusion Models”, Zhicong Tang, Shuyang Gu, Jianmin Bao, Dong Chen, Fang Wen -
https://arxiv.org/abs/2205.11487#google: “Imagen: Photorealistic Text-To-Image Diffusion Models With Deep Language Understanding”, -
https://arxiv.org/abs/2205.07460: “Diffusion Models for Adversarial Purification”, Weili Nie, Brandon Guo, Yujia Huang, Chaowei Xiao, Arash Vahdat, Anima Anandkumar -
https://arxiv.org/abs/2112.10752: “High-Resolution Image Synthesis With Latent Diffusion Models”, Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, Björn Ommer -
https://arxiv.org/abs/2112.05744: “More Control for Free! Image Synthesis With Semantic Diffusion Guidance”, -
https://arxiv.org/abs/2106.09685#microsoft: “LoRA: Low-Rank Adaptation of Large Language Models”, Edward J. Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, Weizhu Chen -
https://cascaded-diffusion.github.io/: “CDM: Cascaded Diffusion Models for High Fidelity Image Generation”, Jonathan Ho, Chitwan Saharia, William Chan, David J. Fleet, Mohammad Norouzi, Tim Salimans -
https://arxiv.org/abs/2105.05233#openai: “Diffusion Models Beat GANs on Image Synthesis”, Prafulla Dhariwal, Alex Nichol -
https://arxiv.org/abs/2104.07636#google: “Image Super-Resolution via Iterative Refinement”, Chitwan Saharia, Jonathan Ho, William Chan, Tim Salimans, David J. Fleet, Mohammad Norouzi -
https://arxiv.org/abs/2102.09672#openai: “Improved Denoising Diffusion Probabilistic Models”, Alex Nichol, Prafulla Dhariwal -
2018-sharma.pdf#google: “Conceptual Captions: A Cleaned, Hypernymed, Image Alt-Text Dataset For Automatic Image Captioning”, Piyush Sharma, Nan Ding, Sebastian Goodman, Radu Soricut -
2011-vincent.pdf: “A Connection Between Score Matching and Denoising Autoencoders”, Pascal Vincent -
https://www.jmlr.org/papers/volume6/hyvarinen05a/hyvarinen05a.pdf: “Estimation of Non-Normalized Statistical Models by Score Matching”, Aapo Hyvärinen