Basic concepts on AIGC
  • About the course materials
  • General Course Format and Strategies
  • Introduction
  • Foundations for AIGC
    • Computers and content generation
    • A brief introduction to AI
      • What AI is?
      • What ML is?
      • What DL is?
      • Discriminative AI vs. Generative AI
  • Generative AI
    • Introduction to Generative AI
      • Going deeper into Generative AI models
  • Deep Neural Networks and content generation
    • Image classification
    • Autoencoders
    • GAN: Generative Adversarial networks
    • Transformers
    • Diffusion models
      • Basic foundations of SD
  • Current image generation techniques
    • GANs
  • Current text generation techniques
    • Basic concepts in NLP in Large Language Models (LLMs)
    • How chatGPT works
  • Prompt engineering
    • Prompts for LLM
    • Prompts for image generators
  • Current AI generative tools
    • Image generation tools
      • DALL-E 2
      • Midjourney
        • More experiments with Midjourney
        • Composition and previous pictures
        • Remixing
      • Stable diffusion
        • Dreambooth
        • Fine-tuning stable diffusion
      • Other solutions
      • Good prompts, img2img, inpainting, outpainting, composition
      • A complete range on new possibilities
    • Text generation tools
      • OpenAI GPT
        • GPT is something really wide
      • ChatGPT
        • Getting the most from chatGPT
      • Other transformers: HuggingFace
      • Other solutions
      • Making the most of LLM
        • Basic possibilities
        • Emergent abilities of LLM
    • Video, 3D, sound, and more
    • Current landscape of cutting-edge AI generative tools
  • Use cases
    • Generating code
    • How to create good prompts for image generation
    • How to generate text of quality
      • Summarizing, rephrasing, thesaurus, translating, correcting, learning languages, etc.
      • Creating/solving exams and tests
  • Final topics
    • AI art?
    • Is it possible to detect AI generated content?
    • Plagiarism and copyright
    • Ethics and bias
    • AI generative tools and education
    • The potential impact of AI generative tools on the job market
  • Glossary
    • Glossary of terms
  • References
    • Main references
    • Additional material
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On this page
  • 3D generation
  • DreamFusion
  • Sound
  • Video
  • Video using stable diffusion
  • 3D generation from few shots: NeRF
  • CLIP interrogation: from pictures to prompts
  • Super Resolution
  1. Current AI generative tools

Video, 3D, sound, and more

PreviousEmergent abilities of LLMNextCurrent landscape of cutting-edge AI generative tools

Last updated 2 years ago

3D generation

DreamFusion

Sound

Video

Video using stable diffusion

3D generation from few shots: NeRF

CLIP interrogation: from pictures to prompts

Super Resolution

Meta:

Phenaki:

https://dreamfusion3d.github.io/
https://makeavideo.studio/
https://phenaki.video/
GitHub - openai/point-e: Point cloud diffusion for 3D model synthesisGitHub
Point E - a Hugging Face Space by openaihuggingface
RiffusionRiffusion
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GitHub - pschaldenbrand/Text2Video: A fast approach for translating a series of text prompts into a video. The 2022 NeurIPS Workshop on Machine Learning for Creativity and DesignGitHub
Making your first AI-generated animation with Deforum Stable DiffusionMedium
NeRF: Neural Radiance FieldsMedium
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CLIP Interrogator - a Hugging Face Space by pharmahuggingface
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What is ‘Image Super Resolution’, and why do we need it?Medium
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