Let's learn about Image Generation via these 52 free blog posts. They are ordered by HackerNoon reader engagement data. Visit the Learn Repo or LearnRepo.com to find the most read blog posts about any technology.
Image generation is the process of creating new images using artificial intelligence or computational methods. It matters for tasks like content creation, synthetic data generation, and design, pushing the boundaries of visual media and creativity across industries.
1. Boosting Your App's Intelligence: Leveraging OpenAI and JS File API
You will learn HOW OpenAI can be leveraged to enhance JS File API on the example of Smart Image Recognition
2. What are the Best Free AI Art Generators of 2023?
Generative AI has made groundbreaking strides in the past few months, and Generative AI models have risen in general popularity.
3. Image Generation: Using Diffusion Networks Explained
I explain how stable diffusion and other diffusion models work.
4. Instagram Is Dead: Here's Why
Santiago explains why Instagram is dead.
5. NVIDIA's Perfusion AI Model Takes Text-to-Image Generation to the Next Level
NVIDIA's new AI model, Perfusion, advances text-to-image generation with enhanced control and fidelity for concept-based visuals.
6. How to Sample From Latent Space With Variational Autoencoder
Explore the unique aspects of VAEs, which separate them from traditional autoencoders by enabling data generation through sampling from a distribution
7. Using CSS to Create a GIF Animation
Using CSS animation to generate the content required for an animated GIF
8. Stuck in Time: Why AI Can’t Stop Drawing Watches at 10:10
Why does AI always draw watches at 10:10? Explore the surprising link between human design, data bias, and AI creativity.
9. AI Image Generation in the HackerNoon Editor (with Stable Diffusion)
Published writers can now generate images using Stable Diffusion!
10. Creating Your Own A.I. Image Generator with Latent-Diffusion
Run your own text to image prompts with CUDA, a bunch of disk space, and an insane amount of memory.
11. Stable Diffusion, Unstable Me: Text-to-image Generation
Text to image generation is not a new idea. What if, you feed <your name> to a state-of-the-art image generation model?
12. How to Run Stable Diffusion on a Mac
This guide covers some of the best ways to run Stable Diffusion locally on a Mac, looking at both no code solutions and solutions that require some code.
13. Nano Banana AI: How to Use Nano Banana for Free
14. A Simple Guide on Crafting Text Prompts for Stable Diffusion Images
Demonstrate a guide on creating unique AI art using Stable Diffusion, by making the best possible prompts yourself.
15. AI Design Tools That are Changing How Graphic Designers Work
AI is here to stay but what impact does it have on the future of graphic design industry.
16. Dall-E May Be Awesome, but It Still Can't Count.
OpenAI's "Dall-E" artificial intelligence can be very frustrating for some professional uses. Here are a few things that Dall-E just can't seem to do.
17. Shutterstock Unleashes the Power of AI With Cutting-Edge Image Generator
Shutterstock's AI image generation can boost creativity by helping users generate images of their own.
18. How to Use Automated Image Generation for Your Business. Get Inspired by Real Examples.
Learn How to Use Automated Image Generation to Increase Traffic, Conversions, and Social Media Visibility? Get inspired by real examples from real businesses...
19. Will Generative Models Be The Next Machine Learning Boom?
Machine Learning is a rapidly growing and very complex field of study. Generative Models might prove to be a new breakthrough that will make a new boom.
20. DALLE 3: Improving Image Generation with Better Captions
OpenAI’s BEST text-to-image model to date!
21. How to Create Beautiful Images from Markdown Text and Tweets
Create beautiful code snippets using markdown text with the help of tweetlet tool. You can also convert tweets and other images with beautiful backgrounds.
22. MindEye2 unCLIP vs. Versatile Diffusion: Evaluating Image Generation from CLIP Latents
To compare the image generation capabilities of our unCLIP model with Versatile Diffusion, we computed Fréchet inception distance (FID)
23. Stable Diffusion Inference Benchmark — 9 Million Images for $1,872 in 24 hrs
In this Stable Diffusion inference benchmark, we scaled up to 750 GPUs, and generated over 9.2 million images in 24 hours for just $1872.
24. 100 Days of AI, Day 20: Using Midjourney for Stock Photos in Your Side Project
Before generative AI, finding stock photos for your side projects was hard, expensive and time consuming.
25. How Consistent ECommerce User-generated Images Help Product Managers Increase Revenue by up to 20%
We’ll be going into the technical side of things, to see what exactly makes visual consistency effective and how it can help your eComm marketplace grow.
26. Decoding Diffusion Models: Core Concepts & PyTorch Code
Explains the mental model behind diffusion models and explains with a simple PyTorch implementation of the same.
27. How to Build a Dynamic Filesystem With FUSE and Node.js: A Practical Approach
Do you ever wonder what happens when you run sshfs user@remote:~/ /mnt/remoteroot? How do files from a remote server appear on your local system and synchronize
28. Introducing the Revamped HackerNoon AI Image Gallery
Explore the revamped HackerNoon AI Image Gallery with more models, creations, and filters. Browse by date, AI model, or keyword to discover AI-driven art.
29. How Online Classifieds Can Innovate With Immersive Technologies
What solutions allow app developers to embed immersive content displaying into a mobile app.
30. FastHTML and Heroku: What You Need to Know
Discover how to build and deploy Python web apps quickly using FastHTML and Heroku. We’ll learn the basics, create an app, and deploy in under 45 seconds!
31. Meta's Emu: The Foundational Model for Emu Edit and Emu Video
Meta's Emu paper unveils revolutionary image generation via quality-tuning, shifting LLMs' paradigm in AI development.
32. Breaking Down Stable Video Diffusion: The Next Frontier in AI Imaging
Stability AI's most recent model Stable Video Diffusion (SVD) explained...
33. Toward Accurate, Realistic Virtual Try-on Through Shape Matching: Abstract & Intro
Researchers improve virtual try-on methods by using a new dataset to choose target models and train specialized warpers, enhancing realism and accuracy.
34. How to Implement AI-Powered Image Generation in the Browser Using React, Vite, and DALL·E
Learn to integrate AI-powered image generation in a React app using OpenAI’s DALL·E API with TypeScript
35. Toward Accurate, Realistic Virtual Try-on Through Shape Matching: Related Work
Researchers improve virtual try-on methods by using a new dataset to choose target models and train specialized warpers, enhancing realism and accuracy.
36. How to Use AI to Create Prompts: A Masterclass in Prompt Engineering
AI prompts are better when created by LLMs. Tell the AI what you want to create and let it generate the prompts for you. The difference is night and day!
37. Olio AI Earns a 43 Proof of Usefulness Score by Building Production-Ready Product Visuals
Olio AI transforms simple product photos into production-ready e-commerce visuals without studios, models, or reshoots cutting costs by up to 100× while scaling
38. SDEdit Helps Regular People Do Complex Graphic Design Tasks
Say goodbye to complex GAN and transformer architectures for image generation. This new method can generate new images from any user-based inputs.
39. Toward Accurate, Realistic Virtual Try-on Through Shape Matching: Proposed Method
Researchers improve virtual try-on methods by using a new dataset to choose target models and train specialized warpers, enhancing realism and accuracy.
40. I Built an AI That Turns Menu Text Into Mouthwatering Food Pics
A weekend AI project that turns menu text into realistic food images using Tesseract, OpenAI, and generative models. Includes GitHub code and live demo.
41. A Reference List to Learn More About Image Editing, Video Editing, and Diffusion Models
Here's a valuable reference list to learn more about diffusion models and image and video editing.
42. Toward Accurate, Realistic Virtual Try-on Through Shape Matching: Experiments
Researchers improve virtual try-on methods by using a new dataset to choose target models and train specialized warpers, enhancing realism and accuracy.
43. ControlNet: Changing The Image Generation Game with Precise Spatial Control
Models like GPT-4V would not have been possible without the idea of ControlNet
44. Toward Accurate, Realistic Virtual Try-on Through Shape Matching: Conclusions & References
Researchers improve virtual try-on methods by using a new dataset to choose target models and train specialized warpers, enhancing realism and accuracy.
45. Fun with Flags: How to Make Flags in C# with Enums and Bit Shifting
Vexillology and Bit Shifting are often not talked about together. Today though, I encode numbers like 52357729848 into country flags using enums in C#.
46. FaceStudio: Put Your Face Everywhere in Seconds: Conclusion and References
A hybrid strategy for text-to-image generation enhances efficiency and identity preservation.
47. FaceStudio: Put Your Face Everywhere in Seconds: Related Work
A hybrid strategy for text-to-image generation enhances efficiency and identity preservation.
48. The AI Monthly Top 3 Papers of October 2021
The 3 most interesting research papers of October 2021!
49. FaceStudio: Put Your Face Everywhere in Seconds: Abstract and Intro
A hybrid strategy for text-to-image generation enhances efficiency and identity preservation.
50. FaceStudio: Put Your Face Everywhere in Seconds: Implementation Details.
A hybrid strategy for text-to-image generation enhances efficiency and identity preservation.
51. FaceStudio: Put Your Face Everywhere in Seconds: Method and Hybrid Guidance Strategy
A hybrid strategy for text-to-image generation enhances efficiency and identity preservation.
52. FaceStudio: Put Your Face Everywhere in Seconds: Results
A hybrid strategy for text-to-image generation enhances efficiency and identity preservation.
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