A Style-Based Generator Architecture for Generative Adversarial Networks
StyleGAN—Official TensorFlow Implementation
Anime Crop Datasets: Faces, Figures, & Hands § Danbooru2019 Portraits
Danbooru2018 Is a Large-Scale Anime Image Database With 3.3m+ Images Annotated With 92.7m+ Tags; It Can Be Useful for Machine Learning Purposes such as Image Recognition and Generation.
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ThisWaifuDoesNotExist.net
This Waifu Does Not Exist
This Anime Does Not Exist.ai (TADNE)
Artbreeder
Making Anime With BigGAN
Large Scale GAN Training for High Fidelity Natural Image Synthesis
Pony Diffusion V6 XL
https://nijijourney.com/en/
Anime Image Generation
https://huggingface.co/hakurei/waifu-diffusion
https://www.reddit.com/r/NovelAi/comments/xu8xpg/novelai_image_generation_launch_announcement/
Waifu Labs
https://crypko.ai/
Generative Adversarial Networks
Improved Techniques for Training GANs
CelebA Dataset
RNN Metadata for Mimicking Author Style
Soumith/dcgan.torch: A Torch Implementation of Https://arxiv.org/abs/1511.06434
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
Danbooru2020 Is a Large-Scale Anime Image Database With 4.2m+ Images Annotated With 130m+ Tags; It Can Be Useful for Machine Learning Purposes such as Image Recognition and Generation.
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A List of All Named GANs!
https://x.com/gwern/status/828311639472611328
https://x.com/gwern/status/828718629181075466
StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks
StackGAN++: Realistic Image Synthesis with Stacked Generative Adversarial Networks
Auto-Regressive Generative Models (PixelRNN, PixelCNN++)
Stabilizing Generative Adversarial Networks: A Survey
Anyone Reproduced the Celeba-HQ Results in the Paper
Synthesizing Programs for Images using Reinforced Adversarial Learning
CAN: Creative Adversarial Networks, Generating "Art" by Learning About Styles and Deviating from Style Norms
Style2Paints GitHub repository
IllustrationGAN: A Simple, Clean TensorFlow Implementation of Generative Adversarial Networks With a Focus on Modeling Illustrations.
MakeGirlsMoe - Create Anime Characters With AI!
Towards the Automatic Anime Characters Creation with Generative Adversarial Networks
Illustration2Vec: a semantic vector representation of illustrations
https://www.reddit.com/r/MachineLearning/comments/akbc11/p_tag_estimation_for_animestyle_girl_image/
Minibatch Discrimination
NoGAN: Decrappification, DeOldification, and Super Resolution
DINO: Emerging Properties in Self-Supervised Vision Transformers
GauGAN Turns Doodles into Stunning, Realistic Landscapes
Semantic Image Synthesis with Spatially-Adaptive Normalization
NVlabs/SPADE: Semantic Image Synthesis With SPADE
Heterochromia
Progressive Growing of GANs for Improved Quality, Stability, and Variation
Progressive Growing of GANs for Improved Quality, Stability, and Variation
ProGAN: Progressive Growing of GANs for Improved Quality, Stability, and Variation [Video]
Improved Precision and Recall Metric for Assessing Generative Models
https://x.com/_Ryobot/status/1095619589495353346
https://x.com/ak92501
https://x.com/_Ryobot
One Limitation of StyleGAN Is That It Generates a ‘Pyramid’ of Images. The First Layer Makes a 4×4 Image, Which Is Upscaled and Passed through the next Layer (8×8), and so On, Until out Pops the Final 1,024×1,024. by the Time You Reach 32×32, the Overall Structure of the Object Is Established (Is This a Face? Is It a Dog?) yet Only the First 4 Layers of the Model Were Allowed to Contribute to That Decision! For a 1,024×1,024 Model, That Means 6 out of 10 Layers of Weights Are Irrelevant.
A Style-Based Generator Architecture for Generative Adversarial Networks [Video]
[StyleGAN] A Style-Based Generator Architecture for GANs, Part 1 (Algorithm Review)
[StyleGAN] A Style-Based Generator Architecture for GANs, Part2 (Results and Discussion)
Styleganportraits.ipynb at Master
GenForce: an Efficient PyTorch Library for Deep Generative Modeling (StyleGANv1v2, PGGAN, Etc)
StyleGAN Made With Keras
https://yippy.ai/skymind
https://www.lyrn.ai/2018/12/26/a-style-based-generator-architecture-for-generative-adversarial-networks/
What Makes a Good Image Generator AI?
On Self Modulation for Generative Adversarial Networks
A Neural Algorithm of Artistic Style
AdaIN: Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization
NVlabs/ffhq-Dataset: Flickr-Faces-HQ Dataset (FFHQ)
https://github.com/FeepingCreature
Interpretation of Discriminator Loss
The relativistic discriminator: a key element missing from standard GAN
Variational Discriminator Bottleneck: Improving Imitation Learning, Inverse RL, and GANs by Constraining Information Flow
https://x.com/davidstap/status/1120667403837423616
Appendix E: Choosing Latent Spaces
idea#better-initializations
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Spectral Norm Regularization for Improving the Generalizability of Deep Learning
Spectral Normalization for Generative Adversarial Networks
Figure 16: (A) A Typical Architectural Layout for BigGAN-Deep’s G
CS231n Convolutional Neural Networks for Visual Recognition
A Technical Report on Convolution Arithmetic in the Context of Deep Learning
Convolution Visualizer
This Person Does Not Exist
Which Face Is Real?
https://blurrd.ai/realorfake/
Judge Fake People
StyleGAN Generates Instagram Portraits AI
https://thesecatsdonotexist.com/
https://thiscatdoesnotexist.com/
GANcats
https://x.com/genekogan/status/1093180351437029376
https://x.com/MichaelFriese10/status/1151236302559305728
https://thisrentaldoesnotexist.com/
https://x.com/crschmidt/status/1099562911960350720
https://x.com/xsteenbrugge/status/1096820308164661248
https://x.com/crschmidt/status/1097200249779769344
https://x.com/refikanadol/status/1106798493299949568
https://x.com/roadrunning01/status/1109488507591028740
https://x.com/erikswahn/status/1123951017148788738
这是一个用StyleGAN训练出的动漫脸生成器
https://x.com/highqualitysh1t/status/1095699293011435520
https://x.com/knjcode/status/1102771002222637056
https://x.com/kikko_fr/status/1094685986691399681
https://imgur.com/a/8nkMmeB
https://x.com/roadrunning01/status/1111686125431783424
https://x.com/MichaelFriese10/status/1127614400750346240
T04glovern/stylegan-Pokemon: Generating Pokemon Cards Using a Mixture of StyleGAN and RNN to Create Beautiful & Vibrant Cards Ready for Battle!
Go Wash Your Hands, Pokemon Generated by Neural Network
GANs Didn’t Fail, They Were Abandoned § Tensorfork Chaos Runs
Here’s a Link to My Colab If You’d like to Give It a Go Yourself. This Codebase Builds off of Previous Work from Many People including @advadnoun @RiversHaveWings @NerdyRodent as well as ClipDraw from @kvfrans @crosslabstokyo @err_more and @okw
Neural Image Generation
CLIP: Connecting Text and Images: We’re introducing a neural network called CLIP which efficiently learns visual concepts from natural language supervision. CLIP can be applied to any visual classification benchmark by simply providing the names of the visual categories to be recognized, similar to the ‘zero-shot’ capabilities of GPT-2 and GPT-3
https://arxiv.org/pdf/2111.01007#page=9
https://x.com/kikko_fr/status/1095603397179396098
A Machine Learning Font
https://towardsdatascience.com/creating-new-scripts-with-stylegan-c16473a50fd0
https://x.com/kintopp/status/1218795800400101376
https://x.com/zaidalyafeai/status/1346841324461416458
https://x.com/PINguAR/status/1097130957163937792
https://x.com/drose101/status/1108104217577832449
https://x.com/mattjarviswall/status/1110548997729452035
Conditional Implementation for NVIDIA’s StyleGAN Architecture
[Seizure Warning] Doom Textures through StyleGAN
Someone Used a Neural Network to Draw Doom Guy in High-Res: A Series of Algorithms Turned the Famous Pixelated Face into an HD Portrait
https://www.reddit.com/r/computervision/comments/bfcnbj/p_stylegan_on_oxford_visual_geometry_group/
This President Does Not Exist: Generating Artistic Portraits of Donald Trump Using StyleGAN Transfer Learning: Theory and Implementation in Tensorflow
I Have No Mana And I Must Tap
https://x.com/ionicdevil/status/1122756808991330304
Eastside Hockey Manager Faces, Colin R. Small
https://www.reddit.com/r/MachineLearning/comments/bkrn3i/p_stylegan_trained_on_album_covers/
Tired of Books Written by Authors? Try Books Written by AI
https://web.archive.org/web/20230604002332/https://thiseyedoesnotexist.com/story/
Curated Output from a StyleGAN 2 Model Trained on Images That Trigger Pareidolia in the Viewer—Scraped from the #iseefaces and #pareidolia Hashtags on Instagram.
https://x.com/MichaelFriese10/status/1130604229372997632
https://x.com/MichaelFriese10/status/1132777932802236417
This Vessel Does Not Exist.
WatchGAN: Advancing Generated Watch Images With StyleGANs
Generating New Watch Designs With StyleGAN
This T-Shirt Does Not Exist
I Trained a StyleGAN on Images of Butterflies from the Natural History Museum in London.
StyleGAN for Evil: Trypophobia and Clockwork Oranging
2020-05-05-tjukanov-mapdreameraicartography.html
End-to-End Chinese Landscape Painting Creation Using Generative Adversarial Networks
Image Data Quilts: Our New Website
Are GANs Created Equal? A Large-Scale Study
ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness
Approximating CNNs with Bag-of-local-Features models works surprisingly well on ImageNet
Robustness properties of Facebook’s ResNeXt WSL models
The Origins and Prevalence of Texture Bias in Convolutional Neural Networks
Large Scale Adversarial Representation Learning
Naoto0804/pytorch-AdaIN: Unofficial Pytorch Implementation of ‘Arbitrary Style Transfer in Real-Time With Adaptive Instance Normalization’ [Huang+, ICCV2017]
E Unibus Pluram: Television and U.S. Fiction
https://openaccess.thecvf.com/content_ICCV_2017/papers/Zhang_StackGAN_Text_to_ICCV_2017_paper.pdf#page=7
https://arxiv.org/pdf/1809.11096.pdf#page=14
https://arxiv.org/pdf/2105.05233.pdf#page=20
https://x.com/kashhill/status/1218542846694871040
GAN Dissection: Visualizing and Understanding Generative Adversarial Networks [Blog]
Spatially Controllable Image Synthesis with Internal Representation Collaging
LARGE: Latent-Based Regression through GAN Semantics
Generative Models: What do they know? Do they know things? Let’s find out!
Rewriting a Deep Generative Model
Unsupervised Discovery of Interpretable Directions in the GAN Latent Space
Object Segmentation Without Labels with Large-Scale Generative Models
Repurposing GANs for One-shot Semantic Part Segmentation
Labels4Free: Unsupervised Segmentation using StyleGAN
DatasetGAN: Efficient Labeled Data Factory with Minimal Human Effort
BigDatasetGAN: Synthesizing ImageNet with Pixel-wise Annotations
Beyond Surface Statistics: Scene Representations in a Latent Diffusion Model
Image2StyleGAN: How to Embed Images Into the StyleGAN Latent Space?
Generative Adversarial Imitation Learning
Enhanced SRGAN. Champion PIRM Challenge on Perceptual Super-Resolution
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
Joeyballentine/ESRGAN: A Modified Version of the Original ESRGAN Test.py Script With Added Features
CC BY-NC 4.0 Deed Attribution-NonCommercial 4.0 International
Nvidia Source Code License
https://x.com/AydaoGMan/status/1269690778324013061
Ffhq-512-Avg-Tpurun1.pkl (348MB)
Comment Regarding Request for Comments on Intellectual Property Protection for Artificial Intelligence Innovation
https://www.copyright.gov/comp3/chap300/ch300-copyrightable-authorship.pdf#Compendium%20300.indd%3A.122046%3A96431
萌えキャラ生成AI、学習データを‘ネットの海’からゲッチュするのはアリか？ (1/5)
https://scholarship.law.duke.edu/cgi/viewcontent.cgi?article=1023&context=dltr#pdf
https://www.rutgerslawreview.com/wp-content/uploads/2017/07/Robert-Denicola-Ex-Machina-69-Rutgers-UL-Rev-251-2016.pdf
https://files.osf.io/v1/resources/np2jd/providers/osfstorage/59614dec594d9002288271b6?action=download&version=1&direct#pdf
https://journal.atp.art/the-next-rembrandt-who-holds-the-copyright-in-computer-generated-art/
The Machine As Author
Why Is AI Art Copyright So Complicated?
We’ve Been Warned about AI and Music for over 50 Years, but No One’s Prepared
https://creativecommons.org/public-domain/cc0/
LSUN Dataset Documentation and Demo Code
LSUN: Construction of a Large-scale Image Dataset using Deep Learning with Humans in the Loop
https://x.com/syoyo/status/1093526177891770369
Amazon EC2 - P2 Instances
Rent GPUs
2019-03-16-gwern-stylegan-facestraining.mp4
Lazy, a tool for running things in idle time
danbooru2021#download
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Nagadomi/lbpcascade_animeface: A Face Detector for Anime/manga Using OpenCV
Nagadomi/waifu2x: Image Super-Resolution for Anime-Style Art
Utility for Working With Danbooru2018 Dataset
Provide Demonstration Script for Producing Images Cropped to the Face
Nagadomi/animeface-2009: Face and Landmark Detector for Anime/Manga. This Is 2009s Version of Imager::AnimeFace, but It Works on Recent System.
Animeface-2009/animeface-Ruby/face_collector.rb at Master
Now Anyone Can Train ImageNet in 18 Minutes
Reimplementation of Https://arxiv.org/abs/1812.04948
Animating GAnime With StyleGAN: Part 1—Introducing a Tool for Interacting With Generative Models
BigGAN: Large Scale GAN Training for High Fidelity Natural Image Synthesis § 4.2 Characterizing Instability: The Discriminator
Deep reinforcement learning from human preferences
Adversarial Examples Are Not Bugs, They Are Features
Image Augmentations for GAN Training
On Data Augmentation for GAN Training
StyleGAN2-ADA: Training Generative Adversarial Networks with Limited Data
Differentiable Augmentation for Data-Efficient GAN Training
Here We Analyze the Performance of BigGAN [2] With Different Amounts of Data on CIFAR-10. As Plotted in Figure 1, Even given 100% Data, the Gap between the Discriminator’s Training and Validation Accuracy Keeps Increasing, Suggesting That the Discriminator Is Simply Memorizing the Training Images...Figure 6 Analyzes That Stronger DiffAugment Policies Generally Maintain a Higher Discriminator’s Validation Accuracy at the Cost of a Lower Training Accuracy, Alleviate the Overfitting Problem, and Eventually Achieve Better Convergence.
Figure 1a Shows Our Baseline Results for Different Subsets of FFHQ. Training Starts the Same Way in Each Case, but Eventually the Progress Stops and FID Starts to Rise. The Less Training Data There Is, the Earlier This Happens. Figure 1b, Figure 1c Shows the Discriminator Output Distributions for Real and Generated Images during Training. The Distributions Overlap Initially but Keep Drifting Apart As the Discriminator Becomes More and More Confident, and the Point Where FID Starts to Deteriorate Is Consistent With the Loss of Sufficient Overlap between Distributions. This Is a Strong Indication of Overfitting, Evidenced Further by the Drop in Accuracy Measured for a Separate Validation Set.
BigGAN: Large Scale GAN Training For High Fidelity Natural Image Synthesis § 5.2 Additional Evaluation On JFT-300M
Do GANs learn the distribution? Some Theory and Empirics
Minibatch Discrimination
KNN-Diffusion: Image Generation via Large-Scale Retrieval
Retrieval-Augmented Diffusion Models: Semi-Parametric Neural Image Synthesis
An analytic theory of creativity in convolutional diffusion models
Novelty Nets: Classifier Anti-Guidance
Styleganime2/misc/ranker.py at Master • Xunings/styleganime2
Discriminator Rejection Sampling
Advanced Machine Learning
This Fursona Does Not Exist
GPT-3 Creative Fiction § Prompts As Programming
Resizing or Scaling—IM V6 Examples
CUDA Toolkit 12.5 Downloads
Install TensorFlow 2
https://colab.research.google.com/notebooks/welcome.ipynb
stylegan/training/training_loop.py
stylegan/train.py at Master • NVlabs
stylegan/train.py at Master
TensorBoard: Visualizing Learning
stylegan/training/training_loop.py
Pastebin
stylegan/train.py at Master
Removing Blob Artifact from StyleGAN Generations without Retraining. Inspired by StyleGAN-2
2019-03-08-Stylegan-Animefaces-Network-02051-021980.pkl
https://arxiv.org/pdf/1809.11096.pdf#page=4
3.1. Style Mixing
Megapixel Size Image Creation using Generative Adversarial Networks
stylegan/pretrained_example.py at Master
generate_figures.py at Master • NVlabs/stylegan
https://x.com/cyrildiagne
https://colab.research.google.com/gist/kikko/d48c1871206fc325fa6f7372cf58db87/stylegan-experiments.ipynb
https://x.com/halcy/status/1098223180454477824
Waifu Synthesis: Real Time Generative Anime
GPT-2 Neural Network Poetry
Magenta
2019-02-14-Stylegan-Faces-02021-010483.tar
2019-02-26-Stylegan-Faces-Network-02048-016041.pkl
twdne#downloads
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https://x.com/SkyLi0n
https://x.com/arfafax/status/1348052573106757636
doc2vec: Distributed Representations of Sentences and Documents
StackGAN: §3.2. Conditioning Augmentation
Conditional Image Generation and Manipulation for User-Specified Content § Pg3
Improved Consistency Regularization for GANs § 2.1 Balanced Consistency Regularization (BCR)
https://cdn.openai.com/papers/Learning_Transferable_Visual_Models_From_Natural_Language_Supervision.pdf#page=4
Contrastive Representation Learning: A Framework and Review
https://colab.research.google.com/drive/1WLU1dIWJ4YeNlMk3Jz9q-1dhLfL23-r-
Cartoon Set
Tag-Based Anime Generation: This Model Uses Doc2vec Embeddings of Danbooru Tags, Combined With a Conditional StyleGAN2 Model, to Generate Anime Characters Based on Tag Inputs.
StyleGAN2_experiments/Preprocess Danbooru Vectors
StyleGAN-2 512px Trained on Danbooru2019
https://x.com/aydaoai
Making Anime With BigGAN § Danbooru2019+e621 256px BigGAN
This Anime Does Not Exist [Blog]
https://x.com/nearcyan
2021-01-19-gwern-stylegan2ext-danbooru2019-3x10montage-1.png
2021-01-19-gwern-stylegan2ext-danbooru2019-3x10montage-2.png
2021-01-19-gwern-stylegan2ext-danbooru2019-3x10montage-3.png
tadne-l4rz-kmeans-k256-n120k-centroidsamples.jpg
Here Are 120K 𝑤 Samples from @AydaoAI’s Large Anime Model (Aka TADNE) Clustered into a Set of 256 Centroids. 𝘸𝘢𝘵𝘤𝘩 𝘪𝘵 𝘴𝘩𝘪𝘯𝘦
Aydao/stylegan2-Surgery
https://colab.research.google.com/drive/1gbqukfE5f4yYOuHWFW-85zuXW8JtWS09
convert_weight.py at Tadne
This Anime Does Not Exist—Interpolation Videos: This Notebook Generates Interpolation Videos from the Model Used for Https://thisanimedoesnotexist.ai by @aydao
https://colab.research.google.com/drive/1QzttnjpQiVHJ8bnhEP0JaSwBX62V1ieG
Scoring images from TADNE with CLIP
This Is Great! Now That the Model Can Be Used in PyTorch, I’ve Starting Playing With @AydaoAI’s Anime StyleGAN Directly Guided by CLIP. Starting Slow by Searching for Asuka by Name in the Latent Space.
StyleGAN Anime Sliders: This Notebook Demonstrate How to Learn and Extract Controllable Directions from ThisAnimeDoesNotExist. This Takes a Pretrained StyleGAN and Uses DeepDanbooru to Extract Various Labels from a Number of Samples. It Then Uses Those Labels to Learn Various Attributes Which Are Controllable With Sliders
https://arxiv.org/pdf/1812.04948.pdf#page=6
https://arxiv.org/pdf/1912.04958.pdf#page=5
Controlled GAN-Based Creature Synthesis via a Challenging Game Art Dataset—Addressing the Noise-Latent Trade-Off
4.1. Simplified Gradient Penalties
Stabilizing Training of Generative Adversarial Networks through Regularization
Update: the XXXL Model (250M Parameters, Doubled Latent Size)
2021-10-12-l4rz-stylegan2-xxxl-cosplayface-snapshot-001360-19520-fid359.pkl
Progressive Growing of GANs for Improved Quality, Stability, and Variation: 3. Increasing Variation Using Minibatch Standard Deviation
TensorFlow Research Cloud (TRC): Accelerate your cutting-edge machine learning research with free Cloud TPUs
Danbooru2019 Is a Large-Scale Anime Image Database With 3.69m+ Images Annotated With 108m+ Tags; It Can Be Useful for Machine Learning Purposes such as Image Recognition and Generation.
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crop#figure
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Anime Crop Datasets: Faces, Figures, & Hands § Hands
Top-K Training of GANs: Improving GAN Performance by Throwing Away Bad Samples
Jukebox: We’re introducing Jukebox, a neural net that generates music, including rudimentary singing, as raw audio in a variety of genres and artist styles. We’re releasing the model weights and code, along with a tool to explore the generated samples.
VQ-GAN: Taming Transformers for High-Resolution Image Synthesis
not-so-BigGAN: Generating High-Fidelity Images on Small Compute with Wavelet-based Super-Resolution
DALL·E 1: Creating Images from Text: We’ve trained a neural network called DALL·E that creates images from text captions for a wide range of concepts expressible in natural language
BigGAN: Non-Normal Latent Space (Binomial Mixture?)
Scaling up StyleGAN-2
‘diffusion model’ directory
Some Heavily Cherrypicked Samples from Transfer Learning Using @AydaoAI’s Enhanced StyleGAN-2 Anime Model After 2 Days.
2020-11-27-aydao-stylegan2ext-danbooru2019s-512px-5268480.pkl
This Anime Does Not Exist
Some AI Koans § Http://www.catb.org/esr/jargon/html/koans.html#id3141241
How I Learned to Stop Worrying and Love Transfer Learning
Image2StyleGAN: How to Embed Images Into the StyleGAN Latent Space? § Pg2
2019-02-10-stylegan-holo-handselectedsamples.zip
Holo Cropped Face Collection
https://www.reddit.com/r/SpiceandWolf/comments/apazs0/my_holo_face_collection/
https://www.reddit.com/r/SpiceandWolf/comments/apbz6r/all_those_cropped_holo_faces_uprimarypizza_posted/
2019-02-10-gwern-stylegan-holofaces-networksnapshot-00015-011370.pkl
2019-02-11-stylegan-asuka-handselectedsamples.zip
https://www.reddit.com/r/evangelion/comments/apmkjm/brighten_your_monday_with_some_asukas_album_of_130/
2019-02-10-gwern-stylegan-asuka-networksnapshot-00025-007903.pkl
https://www.reddit.com/r/MachineLearning/comments/apq4xu/p_stylegan_on_anime_faces/egf8pvt/
Zuihou KanColle Wiki
Akizuki KanColle Wiki
https://x.com/Gansodeva/status/1122361947410849792
Arknights
https://www.reddit.com/r/MachineLearning/comments/apq4xu/p_stylegan_on_anime_faces/egmyf60/
FGO StyleGAN: This Heroic Spirit Doesn’t Exist
https://x.com/roadrunning01/status/1097513035474845696
https://x.com/FlatIsNice/status/1112671357706424322
Asashio KanColle Wiki
This Asashio Does Not Exist
https://x.com/__meimiya__/status/1102679068242173952
https://x.com/__meimiya__/status/1134441616477806592
https://x.com/__meimiya__/status/1134751068758265856
https://www.reddit.com/r/touhou/comments/gl180j/here_have_a_few_marisa_portraits/
A Few Marisa Portraits
https://x.com/3D_DLW/status/1227313334237745155
微调StyleGAN2模型
微调StyleGAN2模型(使用Google Colab)_微调styglegan2
Warship Girls (Video Game)
Played around With @gwern’s TWDNEv2 Model to Generate Images of Hayasaka Ai! This Is After ~9 Hours of Training (n = 300+). Stopped Working on It After a Bit, so a Bunch of Potential Improvements. More Thoughts Here: https://github.com/ZKTKZ/thdne/bl
Hayasaka.ai/StyleGAN2_Tazik_25GB_RAM.ipynb at Master • Taziksh/hayasaka.ai
Stylegan Neural Ahegao
Andy8744 Expert
https://www.kaggle.com/datasets/andy8744/rezero-rem-anime-faces-for-gan-training
https://www.kaggle.com/code/andy8744/predict-anime-face-using-pre-trained-model/data
https://github.com/ultralytics/yolov5/issues/6998#issue-1170533269
Rem
https://www.youtube.com/watch?v=D2zjc--sDaY
https://x.com/lord_yuanyuan
https://www.kaggle.com/code/andy8744/generating-ganyu-from-trained-model/notebook
Ganyu Genshin Impact Wiki
https://x.com/sunkworld/status/1100954144905543680
https://x.com/misaki_cradle
1996-sadamoto-howtodrawshinjinadia.jpg
2019-05-06-stylegan-malefaces-1ksamples.tar
https://x.com/Buntworthy/status/1213402237269159936
Ukiyo-e Search
https://x.com/AydaoGMan/status/1217276442230378497
ArtGAN/WikiArt Dataset
GAN Explorations 011: StyleGAN2 + Stochastic Weight Averaging
Averaging Weights Leads to Wider Optima and Better Generalization
StyleGAN Samples
StyleGAN network blending
Toonify: Resolution Dependent GAN Interpolation for Controllable Image Synthesis Between Domains
StyleGAN2 Blending of Humans With Cartoons
‘Network Blending in StyleGAN: Swapping Layers between Two Models in StyleGAN Gives Some Interesting Results. You Need a Base Model and a Second Model Which Has Been Fine-Tuned from the Base.’, Buntworthy
I Just Tried My StyleGAN Layer Swapping Method the Other Way round to What I’d Been Doing Before. So Making the Ukiyo-E Model Human (Rather Than the Other Way Around) and I Love the Results!
Combining My Cross-Model Interpolation With @Buntworthy‘s Layer Swapping Idea. Here the Different Resolution Layers Are Being Interpolated at Different Rates between Furry, FFHQ, and @KitsuneKey’s Foxes. P0 Is 4x4 and 8x8, P1 Is 16x16 to 128x128, and P2 Is 256x256 to 512x512.
Cross-Model Interpolations Are One of Those Neat Hidden Features That Arise from Transfer Learning. Here I‘M Interpolating between 5 StyleGAN2 Models: Furry, FFHQ, Anime, Ponies, and @KitsuneKey’s Fox Model. All Were Trained off the Same Base Model, Which Makes Blending Possible.
Imagined Visage
https://x.com/pbaylies/status/1136307166695108609
Discovering Interpretable GAN Controls
Adversarial Feature Learning
Inverting The Generator Of A Generative Adversarial Network (II)
Reinventing the Wheel: Discovering the Optimal Rolling Shape With PyTorch
Galton Boards Are Fun and All, but What about Asymmetric Galton Board 🎉😇 By Tuning (Thanks #autodiff!) the Probabilities of Going to the Left/right, One Can Pretty Much Obtain Any Desired Final Distribution 😍 #probability #python #jax
Mining gold from implicit models to improve likelihood-free inference
Gradient Theory of Optimal Flight Paths
A Steepest-Ascent Method for Solving Optimum Programming Problems
Deep Set Prediction Networks
Synthesizing the preferred inputs for neurons in neural networks via deep generator networks
Unadversarial Examples: Designing Objects for Robust Vision
Image Synthesis from Yahoo’s open_nsfw
Ambigrammatic Figures: 55 Grotesque Ambigrams
Amplifying The Uncanny § Pg5
Differentiable Image Parameterizations
Style Generator Inversion for Image Enhancement and Animation
Style Generator Inversion for Image Enhancement and Animation
On the "steerability" of generative adversarial networks
Interpreting the Latent Space of GANs for Semantic Face Editing
Deep Danbooru
SummitKwan/transparent_latent_gan: Use Supervised Learning to Illuminate the Latent Space of GAN for Controlled Generation and Edit
https://www.kaggle.com/summitkwan/tl-gan-demo
Generating Custom Photo-Realistic Faces Using AI: Controlled Image Synthesis and Editing Using a Novel (Transparent Latent-Space GAN) TL-GAN Model
StyleGAN Encoder—Converts Real Images to Latent Space
https://www.reddit.com/r/MachineLearning/comments/aq6jxf/p_stylegan_encoder_from_real_images_to_latent/
StyleGAN Encoder—Converts Real Images to Latent Space
https://github.com/Puzer/stylegan-encoder-encoder/blob/master/Play_with_latent_directions.ipynb
https://x.com/halcy
StyleGAN—Official TensorFlow Implementation
https://imgur.com/d8EYyel
https://imgur.com/BLWbiXT
Stylegan-Generate-Encode.ipynb at Master
https://colab.research.google.com/drive/1LiWxqJJMR5dg4BxwUgighaWp2U_enaFd#offline=true&sandboxMode=true
Icosahedron
https://www.reddit.com/r/AnimeResearch/comments/aul582/modification_of_anime_face_stylegan_disentangled/
2020-snowyhalcy-stylegan-animefaceediting-brightness.png
Interactive Waifu Modification
https://www.youtube.com/watch?v=GRG6czAZql0
StyleGAN—Official TensorFlow Implementation
https://www.reddit.com/r/MediaSynthesis/comments/c6axmr/close_the_world_txen_eht_nepo/
This Anime Does Not Exist [Video]
https://x.com/Artbreeder/status/1182293849181495296
https://x.com/arfafax/status/1263638042889224193
This Fursona Does Not Exist—Fursona Editor (Tensorflow Version)
This Pony Does Not Exist
GANSpace: Discovering Interpretable GAN Controls
https://x.com/realmeatyhuman/status/1255570195319590913
https://colab.research.google.com/drive/1g-ShMzkRWDMHPyjom_p-5kqkn2f-GwBi
This Waifu Does Not Exist § TWDNEv3
StyleGAN-2—Official TensorFlow Implementation
StyleGAN-2-ADA—Official PyTorch Implementation
StyleGAN2
MSG-GAN: Multi-Scale Gradients for Generative Adversarial Networks
2020-01-11-skylion-stylegan2-animeportraits-networksnapshot-024664.pkl
https://hivemind-repo.s3-us-west-2.amazonaws.com/twdne3/twdne3.pt
https://hivemind-repo.s3-us-west-2.amazonaws.com/twdne3/twdne3.onnx
Implementation of Analyzing and Improving the Image Quality of StyleGAN (StyleGAN 2) in PyTorch
https://colab.research.google.com/drive/1Pv8OIFlonha4KeYyY2oEFaK4mG-alaWF
https://x.com/layolu/status/1218177246495535104
https://x.com/theshawwn/status/1230022825538248704
StyleGAN-2—Official TensorFlow Implementation
StyleGAN → BigGAN: Import the StyleGAN Large 8x512 FC z → w Embedding Trick
Minibatch Discrimination
EndingCredits/Set-CGAN: Adaptation of Conventional GAN to Condition on Additional Input Set
FIGR: Few-shot Image Generation with Reptile
Few-Shot Unsupervised Image-to-Image Translation
Image Generation From Small Datasets via Batch Statistics Adaptation
YFCC100M: The New Data in Multimedia Research
Evolving Normalization-Activation Layers
https://www.reddit.com/r/MachineLearning/comments/e23ezq/p_using_stylegan_to_make_a_music_visualizer/
Pretrained Anime StyleGAN-2: Convert to Pytorch and Editing Images by Encoder by Allen Ng Pickupp
Video Shows off Hundreds of Beautiful AI-Created Anime Girls in Less Than a Minute
Talking Head Anime from a Single Image
https://podgorskiy.com/static/stylegan/stylegan.html
Unofficial Implementation of StyleGAN’s Generator
StyleGAN-2—Official TensorFlow Implementation
https://towardsdatascience.com/stylegan-v2-notes-on-training-and-latent-space-exploration-e51cf96584b3
Practical aspects of StyleGAN2 training
Morphing Anime Girls Quiz
https://amitness.com/posts/google-colab-tips
Deep Generative Modeling: A Comparative Review of VAEs, GANs, Normalizing Flows, Energy-Based and Autoregressive Models
State-Of-The-Art Image Generative Models
Generative Modeling by Estimating Gradients of the Data Distribution
[P] StyleGAN on Anime Faces
Генерация Аниме С Помощью Нейросети StyleGAN
