“‘StyleGAN’ Tag”,2019-09-13 (BigGAN)⁠:

Bibliography for tag ai/nn/gan/stylegan, most recent first: 5 related tags, 142 annotations, & 50 links (parent).

• See Also
• Links
  • “Machine Learning As a Tool for Hypothesis Generation”, Jens & Sendhil2024
  • “The Spontaneous Emergence of ‘A Sense of Beauty’ in Untrained Deep Neural Networks”, Shu et al 2024
  • “Generative Models: What Do They Know? Do They Know Things? Let’s Find Out!”, Du et al 2023
  • “Concept Sliders: LoRA Adaptors for Precise Control in Diffusion Models”, Gandikota et al 2023
  • “Rosetta Neurons: Mining the Common Units in a Model Zoo”, Dravid et al 2023
  • “Exposing Flaws of Generative Model Evaluation Metrics and Their Unfair Treatment of Diffusion Models”, Stein et al 2023
  • “Drag Your GAN (DragGAN): Interactive Point-Based Manipulation on the Generative Image Manifold”, Pan et al 2023
  • “Realistic Face Reconstruction from Deep Embeddings”, Vendrow & Vendrow2023
  • “SAN: Inducing Metrizability of GAN With Discriminative Normalized Linear Layer”, Takida et al 2023
  • “StyleGAN-T: Unlocking the Power of GANs for Fast Large-Scale Text-To-Image Synthesis”, Sauer et al 2023
  • “Brain2GAN: Reconstructing Perceived Faces from the Primate Brain via StyleGAN3”, Anonymous2022
  • “Fast Text2StyleGAN: Text-Free Learning of a Natural Language Interface for Pretrained Face Generators”, Du et al 2022
  • “User-Controllable Latent Transformer for StyleGAN Image Layout Editing”, Endo2022
  • “Generator Knows What Discriminator Should Learn in Unconditional GANs”, Lee et al 2022
  • “CelebV-HQ: A Large-Scale Video Facial Attributes Dataset”, Zhu et al 2022
  • “InfiniteNature-Zero: Learning Perpetual View Generation of Natural Scenes from Single Images”, Li et al 2022
  • “BigVGAN: A Universal Neural Vocoder With Large-Scale Training”, Lee et al 2022
  • “Diffusion-GAN: Training GANs With Diffusion”, Wang et al 2022
  • “StyleGAN-Human: A Data-Centric Odyssey of Human Generation”, Fu et al 2022
  • “Polarity Sampling: Quality and Diversity Control of Pre-Trained Generative Networks via Singular Values”, Humayun et al 2022
  • “State-Of-The-Art in the Architecture, Methods and Applications of StyleGAN”, Bermano et al 2022
  • “AI-Synthesized Faces Are Indistinguishable from Real Faces and More Trustworthy”, Nightingale & Farid2022
  • “StyleGAN-XL: Scaling StyleGAN to Large Diverse Datasets”, Sauer et al 2022
  • “StyleGAN-V: A Continuous Video Generator With the Price, Image Quality and Perks of StyleGAN-2”, Skorokhodov et al 2021
  • “Efficient Geometry-Aware 3D Generative Adversarial Networks”, Chan et al 2021
  • “CLIP2StyleGAN: Unsupervised Extraction of StyleGAN Edit Directions”, Abdal et al 2021
  • “HyperStyle: StyleGAN Inversion With HyperNetworks for Real Image Editing”, Alaluf et al 2021
  • “LAFITE: Towards Language-Free Training for Text-To-Image Generation”, Zhou et al 2021
  • “Improving Visual Quality of Image Synthesis by A Token-Based Generator With Transformers”, Zeng et al 2021
  • “StyleCLIPDraw: Coupling Content and Style in Text-To-Drawing Synthesis”, Schaldenbrand et al 2021
  • “StyleAlign: Analysis and Applications of Aligned StyleGAN Models”, Wu et al 2021
  • “Pose With Style: Detail-Preserving Pose-Guided Image Synthesis With Conditional StyleGAN”, AlBahar et al 2021
  • “Controlled GAN-Based Creature Synthesis via a Challenging Game Art Dataset—Addressing the Noise-Latent Trade-Off”, Vavilala & Forsyth2021
  • “LARGE: Latent-Based Regression through GAN Semantics”, Nitzan et al 2021
  • “Alias-Free Generative Adversarial Networks”, Karras et al 2021
  • “Lazy, a Tool for Running Things in Idle Time”, nshepperd 2021
  • “Exploiting Spatial Dimensions of Latent in GAN for Real-Time Image Editing”, Kim et al 2021
  • “Explaining in Style: Training a GAN to Explain a Classifier in StyleSpace”, Lang et al 2021
  • “DatasetGAN: Efficient Labeled Data Factory With Minimal Human Effort”, Zhang et al 2021
  • “Labels4Free: Unsupervised Segmentation Using StyleGAN”, Abdal et al 2021
  • “Repurposing GANs for One-Shot Semantic Part Segmentation”, Tritrong et al 2021
  • “Generative Adversarial Transformers”, Hudson & Zitnick2021
  • “Generating Images from Caption and vice Versa via CLIP-Guided Generative Latent Space Search”, Galatolo et al 2021
  • “Not-So-BigGAN: Generating High-Fidelity Images on Small Compute With Wavelet-Based Super-Resolution”, Han et al 2020
  • “Rewriting a Deep Generative Model”, Bau et al 2020
  • “Differentiable Augmentation for Data-Efficient GAN Training”, Zhao et al 2020
  • “StyleGAN-2-ADA: Training Generative Adversarial Networks With Limited Data”, Karras et al 2020
  • “On Data Augmentation for GAN Training”, Tran et al 2020
  • “Image Augmentations for GAN Training”, Zhao et al 2020
  • “Ambigrammatic Figures: 55 Grotesque Ambigrams”, Levin & Huang2020
  • “Practical Aspects of StyleGAN-2 Training”, l4rz 2020
  • “GANSpace: Discovering Interpretable GAN Controls”, Härkönen et al 2020
  • “Evolving Normalization-Activation Layers”, Liu et al 2020
  • “Top-K Training of GANs: Improving GAN Performance by Throwing Away Bad Samples”, Sinha et al 2020
  • “Unsupervised Discovery of Interpretable Directions in the GAN Latent Space”, Voynov & Babenko2020
  • “Conditional Image Generation and Manipulation for User-Specified Content § Pg3”, Stap2020 (page 3)
  • “Analyzing and Improving the Image Quality of StyleGAN”, Karras et al 2019
  • “Detecting GAN Generated Errors”, Zhu et al 2019
  • “Seeing What a GAN Cannot Generate”, Bau et al 2019
  • “Stabilizing Generative Adversarial Networks: A Survey”, Wiatrak et al 2019
  • “Interpreting the Latent Space of GANs for Semantic Face Editing”, Shen et al 2019
  • “On the “Steerability” of Generative Adversarial Networks”, Jahanian et al 2019
  • “Style Generator Inversion for Image Enhancement and Animation”, Gabbay & Hoshen2019
  • “NoGAN: Decrappification, DeOldification, and Super Resolution”, Antic et al 2019
  • “Improved Precision and Recall Metric for Assessing Generative Models”, Kynkäänniemi et al 2019
  • “Image2StyleGAN: How to Embed Images Into the StyleGAN Latent Space?”, Abdal et al 2019
  • “The Machine As Author”, Gervais2019
  • “MSG-GAN: Multi-Scale Gradients for Generative Adversarial Networks”, Karnewar & Wang2019
  • “This Person Does Not Exist”, Wang2019
  • “FIGR: Few-Shot Image Generation With Reptile”, Clouâtre & Demers2019
  • “A Style-Based Generator Architecture for Generative Adversarial Networks”, Karras et al 2018
  • “GAN Dissection: Visualizing and Understanding Generative Adversarial Networks”, Bau et al 2018
  • “Discriminator Rejection Sampling”, Azadi et al 2018
  • “On Self Modulation for Generative Adversarial Networks”, Chen et al 2018
  • “Variational Discriminator Bottleneck: Improving Imitation Learning, Inverse RL, and GANs by Constraining Information Flow”, Peng et al 2018
  • “Inverting The Generator Of A Generative Adversarial Network (II)”, Creswell & Bharath2018
  • “Megapixel Size Image Creation Using Generative Adversarial Networks”, Marchesi2017
  • “AdaIN: Arbitrary Style Transfer in Real-Time With Adaptive Instance Normalization”, Huang & Belongie2017
  • “StackGAN: Text to Photo-Realistic Image Synthesis With Stacked Generative Adversarial Networks”, Zhang et al 2016
  • “Ukiyo-E Search”, Resig2013
  • “Deep Danbooru”
  • “GAN Dissection: Visualizing and Understanding Generative Adversarial Networks [Blog]”
  • “WatchGAN: Advancing Generated Watch Images With StyleGANs”
  • “Generating New Watch Designs With StyleGAN”
  • “StyleGAN—Official TensorFlow Implementation”
  • “EndingCredits/Set-CGAN: Adaptation of Conventional GAN to Condition on Additional Input Set”
  • “convert_weight.py at Tadne”
  • “Joeyballentine/ESRGAN: A Modified Version of the Original ESRGAN Test.py Script With Added Features”
  • “StyleGAN—Official TensorFlow Implementation”
  • “generate_figures.py at Master · NVlabs/stylegan”
  • “stylegan/pretrained_example.py at Master”
  • “stylegan/train.py at Master · NVlabs”
  • “stylegan/train.py at Master”
  • “stylegan/train.py at Master”
  • “stylegan/training/training_loop.py”
  • “stylegan/training/training_loop.py”
  • “StyleGAN-2—Official TensorFlow Implementation”
  • “StyleGAN-2-ADA—Official PyTorch Implementation”
  • “Official PyTorch Implementation of StyleGAN3”
  • “StyleGAN Encoder—Converts Real Images to Latent Space”
  • “Styleganportraits.ipynb at Master”
  • “Implementation of Analyzing and Improving the Image Quality of StyleGAN (StyleGAN 2) in PyTorch”
  • “Preprocess Danbooru Vectors—StyleGAN Conditional”
  • “Style Generator Inversion for Image Enhancement and Animation”
  • “Aydao/stylegan2-Surgery”
  • “Conditional Implementation for NVIDIA’s StyleGAN Architecture”
  • “ArtGAN/WikiArt Dataset”
  • “StyleGAN—Official TensorFlow Implementation”
  • “Stylegan-Generate-Encode.ipynb at Master”
  • “StyleGAN Made With Keras”
  • “Interpretation of Discriminator Loss”
  • “GAN’s N’ Roses. Diverse Im2im and Vid2vid Selfie to Anime Translation.”
  • “StyleGAN-2—Official TensorFlow Implementation”
  • “Reimplementation of Https://arxiv.org/abs/1812_212ya.04948”
  • “StyleGAN Encoder—Converts Real Images to Latent Space”
  • “Unofficial Implementation of StyleGAN’s Generator”
  • “StyleGAN-2—Official TensorFlow Implementation”
  • “T04glovern/stylegan-Pokemon: Generating Pokemon Cards Using a Mixture of StyleGAN and RNN to Create Beautiful & Vibrant Cards Ready for Battle!”
  • “Hayasaka.ai/StyleGAN-2_Tazik_25GB_RAM.ipynb”
  • “IllustrationGAN: A Simple, Clean TensorFlow Implementation of Generative Adversarial Networks With a Focus on Modeling Illustrations.”
  • “Semantic Image Editing in Realtime With a Multi-Parameter Interface for StyleCLIP Global Directions”
  • “Progressive Growing of GANs for Improved Quality, Stability, and Variation”
  • “Enhanced SRGAN. Champion PIRM Challenge on Perceptual Super-Resolution”
  • “Styleganime2/misc/ranker.py at Master · Xunings/styleganime2”
  • “This President Does Not Exist: Generating Artistic Portraits of Donald Trump Using StyleGAN Transfer Learning: Theory and Implementation in Tensorflow”
  • “Pretrained Anime StyleGAN-2: Convert to Pytorch and Editing Images by Encoder by Allen Ng Pickupp”
  • “Network-Snapshot-057891.pkl”
  • “Nvidia Source Code License”
  • “TensorFlow Research Cloud (TRC): Accelerate Your Cutting-Edge Machine Learning Research With Free Cloud TPUs”, TRC 2024
  • “Video Shows off Hundreds of Beautiful AI-Created Anime Girls in Less Than a Minute”
  • “StyleGAN for Evil: Trypophobia and Clockwork Oranging”
  • “This Anime Does Not Exist”
  • “Waifu Synthesis: Real Time Generative Anime”
  • “How I Learned to Stop Worrying and Love Transfer Learning”
  • “Stylegan Neural Ahegao”
  • “Removing Blob Artifact from StyleGAN Generations without Retraining. Inspired by StyleGAN-2”
  • “I Trained a StyleGAN on Images of Butterflies from the Natural History Museum in London.”
  • “A Style-Based Generator Architecture for Generative Adversarial Networks [Video]”
  • “Random Walk StyleGAN”
  • Buntworthy
  • TacoCohen
  • “StyleGAN Samples”
  • Sort By Magic
    • face-generation
    • data-augmentation
    • stylegan-control
    • stylegan-improvement
    • ambigram
• Miscellaneous
• Bibliography