“‘Anime AI’ Tag”,2019-09-30 (Japan)⁠:

Bibliography for tag ai/anime, most recent first: 6 related tags, 86 annotations, & 87 links (parent).

• See Also
• Links
  • “Computer-Aided Colorization State-Of-The-Science: A Survey”, Cao et al 2024
  • “Improvements to SDXL in NovelAI Diffusion V3”, Ossa et al 2024
  • “The Rise of Terminator Zero With Writer Mattson Tomlin & Director Masashi Kudo”, Baron2024
  • “NovelAI Diffusion V1 Weights Release”, NovelAI 2024
  • “Tails Tell Tales: Chapter-Wide Manga Transcriptions With Character Names”, Sachdeva et al 2024
  • “Sakuga-42M Dataset: Scaling Up Cartoon Research”, Pan et al 2024
  • “Zero-Shot Character Identification and Speaker Prediction in Comics via Iterative Multimodal Fusion”, Li et al 2024
  • “Hierarchical Feature Warping and Blending for Talking Head Animation”, Zhang et al 2024
  • “APISR: Anime Production Inspired Real-World Anime Super-Resolution”, Wang et al 2024
  • “The Manga Whisperer: Automatically Generating Transcriptions for Comics”, Sachdeva & Zisserman2024
  • “Introducing NovelAI Diffusion Anime V3”, NovelAI 2023
  • “Abstraction-Perception Preserving Cartoon Face Synthesis”, Ho et al 2023
  • “Overview of Cartoon Face Generation”, Shen et al 2023
  • “StencilTorch: An Iterative and User-Guided Framework for Anime Lineart Colorization”, Hati et al 2023
  • “Reference Based Sketch Extraction via Attention Mechanism”, Ashtari et al 2022
  • “AnimeRun: 2D Animation Visual Correspondence from Open Source 3D Movies”, Siyao et al 2022
  • “Deep Learning for Image Colorization: Current and Future Prospects”, Huang et al 2022b
  • “Using Generative Adversarial Networks for Conditional Creation of Anime Posters”, Sankalpa et al 2022
  • “AnimeSR: Learning Real-World Super-Resolution Models for Animation Videos”, Wu et al 2022
  • “Towards Layer-Wise Image Vectorization”, Ma et al 2022
  • “Learning to Generate Artistic Character Line Drawing”, Fang et al 2022
  • “A Challenging Benchmark of Anime Style Recognition”, Li et al 2022
  • “Fast Text Placement Scheme for ASCII Art Synthesis”, Chung & Kwon2022
  • “KNN-Diffusion: Image Generation via Large-Scale Retrieval”, Ashual et al 2022
  • “Make-A-Scene: Scene-Based Text-To-Image Generation With Human Priors”, Gafni et al 2022
  • “Learning to Generate Line Drawings That Convey Geometry and Semantics”, Chan et al 2022
  • “CAST: Character Labeling in Animation Using Self-Supervision by Tracking”, Nir et al 2022
  • “Intelli-Paint: Towards Developing Human-Like Painting Agents”, Singh et al 2021
  • “AnimeCeleb: Large-Scale Animation CelebHeads Dataset for Head Reenactment”, Kim et al 2021
  • “Learning a Perceptual Manifold With Deep Features for Animation Video Resequencing”, Morace et al 2021
  • “GANs N’ Roses: Stable, Controllable, Diverse Image to Image Translation (works for Videos Too!)”, Chong & Forsyth2021
  • “Towards Fully Automated Manga Translation”, Hinami et al 2020
  • “The 2020s Political Economy of Machine Translation”, Weber2020
  • “Pony Voice Event—What People Forced Ponies to Say!”, Daily 2020
  • “E621 Face Dataset”, Arfafax2020
  • “Why Do Line Drawings Work? A Realism Hypothesis”, Hertzmann2020
  • “StarGAN Based Facial Expression Transfer for Anime Characters”, Mobini & Ghaderi2020
  • “SketchTransfer: A Challenging New Task for Exploring Detail-Invariance and the Abstractions Learned by Deep Networks”, Lamb et al 2019
  • “PaintsTorch: a User-Guided Anime Line Art Colorization Tool With Double Generator Conditional Adversarial Network”, Hati et al 2019
  • “Generating Furry Face Art from Sketches Using a GAN”, Yu2019
  • “ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks”, Wang et al 2018
  • “Twin-GAN: Unpaired Cross-Domain Image Translation With Weight-Sharing GANs”, Li2018
  • “Cartoon Set”, Royer et al 2018
  • “Anime Style Space Exploration Using Metric Learning and Generative Adversarial Networks”, Xiang & Li2018
  • “Progressive Growing of GANs for Improved Quality, Stability, and Variation”, Karras et al 2017
  • “Using Posters to Recommend Anime and Mangas in a Cold-Start Scenario”, Vie et al 2017
  • “Towards the Automatic Anime Characters Creation With Generative Adversarial Networks”, Jin et al 2017
  • “BAM! The Behance Artistic Media Dataset for Recognition Beyond Photography”, Wilber et al 2017
  • “Pix2Pix: Image-To-Image Translation With Conditional Adversarial Networks”, Isola et al 2016
  • “Illustration2Vec: a Semantic Vector Representation of Illustrations”, Masaki & Matsui2015
  • “Sketch-Based Manga Retrieval Using Manga109 Dataset”, Matsui et al 2015
  • “Towards Pony Diffusion V7, Going With the Flow.”, AstraliteHeart2024
  • “WatchGAN: Advancing Generated Watch Images With StyleGANs”
  • “Faces2Anime: Cartoon Style Transfer in Faces Using Generative Adversarial Networks”
  • “EndingCredits/Set-CGAN: Adaptation of Conventional GAN to Condition on Additional Input Set”
  • “Joeyballentine/ESRGAN: A Modified Version of the Original ESRGAN Test.py Script With Added Features”
  • “BigGAN-PyTorch: The Author’s Officially Unofficial PyTorch BigGAN Implementation”
  • “Akanimax/Variational_Discriminator_Bottleneck: Implementation (with Some Experimentation) of the Paper Titled “Variational Discriminator Bottleneck””
  • “MSG-GAN: Multi-Scale Gradients GAN (Architecture Inspired from ProGAN but Doesn’t Use Layer-Wise Growing)”
  • “Preprocess Danbooru Vectors—StyleGAN Conditional”
  • “Real-CUGAN/README_EN.md”
  • “Conditional Implementation for NVIDIA’s StyleGAN Architecture”
  • “V Objective Diffusion Inference Code for PyTorch”
  • “ArtGAN/WikiArt Dataset”
  • “Junyanz/CycleGAN: Software That Can Generate Photos from Paintings, Turn Horses into Zebras, Perform Style Transfer, and More.”
  • “StyleGAN Made With Keras”
  • “Martinarjovsky/WassersteinGAN”
  • “Interpretation of Discriminator Loss”
  • “Code for Reproducing Results in “Glow: Generative Flow With Invertible 1×1 Convolutions””
  • “Unofficial Implementation of StyleGAN’s Generator”
  • “A List of Papers and Other Resources on Computer Vision and Deep Learning With Anime Style Images”
  • “Pytorch Implementation of ‘Large Scale GAN Training For High Fidelity Natural Image Synthesis’ (BigGAN)”
  • “Simple Tensorflow Implementation of “Large Scale GAN Training for High Fidelity Natural Image Synthesis” (BigGAN)”
  • “Simple Tensorflow Implementation of “Self-Attention Generative Adversarial Networks” (SAGAN)”
  • “Hayasaka.ai/StyleGAN-2_Tazik_25GB_RAM.ipynb”
  • “IllustrationGAN: A Simple, Clean TensorFlow Implementation of Generative Adversarial Networks With a Focus on Modeling Illustrations.”
  • “Enhanced SRGAN. Champion PIRM Challenge on Perceptual Super-Resolution”
  • “Real-ESRGAN/docs/anime_video_model.md at Master”
  • “PaintsUndo: A Base Model of Drawing Behaviors in Digital Paintings”
  • “Glow: Better Reversible Generative Models”
  • “Video Shows off Hundreds of Beautiful AI-Created Anime Girls in Less Than a Minute”
  • “This Anime Does Not Exist”
  • “MASSIVE 💥 DALL·E 2 ANIME ⚡︎ KEYWORDS + MODIFIERS LIST ★ : Haaaaven”
  • “Waifu Synthesis: Real Time Generative Anime”
  • “The Rise of Anime Generating AI”
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