Exploring AI Image Generators:
Benefits, Types, and Use Cases

5 Benefits of Using AI Image Generators

Here are the top five reasons why you should consider using tools like Depositphotos AI Image Generator, available at https://depositphotos.com/ai-image-generator.html, for professional and personal creative purposes.

1. They are cost-effective. If you don’t have a budget to hire a professional photographer, designer, or illustrator, you can opt for an AI image generator This is a budget-friendly solution for small businesses, startups, or independent creators.
2. They are quick to deliver results—in fact, much faster than traditional methods. The latest updates allow tools like Stable Diffusion and DALL-E to generate visuals 30 times faster, delivering high-quality results in seconds or minutes. This makes them a great option for those who have tight deadlines or simply want to streamline the content creation process and achieve faster project turnarounds.

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3. They are flexible. AI image generators allow users to experiment with different styles, themes, and effects easily. This allows you to create unique visuals that might be challenging or time-consuming to produce manually, and customize them as much as you need.
4. They are user-friendly. Often, it’s enough to write a simple text prompt to obtain a visual right away. Due to that, they are easy to use even by those who don’t have a background in art, design, or photography.
5. They can be consistent in style and quality. Users can create visuals that look or feel similar, and use them for branding and to ensure cohesive aesthetics across different projects.

Types of AI Image Generators

As mentioned above, there are different types of such tools, so how can you choose the best AI image generator for your needs? Read further to discover their most common types and pick the most straightforward one for your project.

1. Text-to-Image AI Generators

These tools create images based on descriptive text prompts provided by a user. The AI generates visuals that match the given description, which can range from realistic photos to abstract illustrations.

This is one of the most popular types of such tools, and the numbers prove that: there were over 15 billion images created using text-to-image algorithms from 2022 to 2023, a number that took dozens of years for photographers to reach. The most prominent examples of these platforms are Depositphotos AI Image Generator, DALL-E, Midjourney, and Stable Diffusion. Most often, they are used for creative art projects, concept art, marketing visuals, and social media content.

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2. Image-to-Image AI Generators

These generators modify or transform an existing image based on a visual that a user uploads. This visual could be a simple sketch, photo, or another image that the AI uses to create a refined or stylized version.

The most prominent examples of such tools are DeepArt, Artbreeder, and Stable Diffusion (image-to-image mode). They are often used for photo enhancement, style transfer, adding artistic effects, or generating variations of an existing design.

3. Inpainting and Outpainting AI Generators

They are used to add something to an existing image. For instance, inpainting is the process of filling in missing or damaged parts of an image with the help of AI technology. Outpainting, on the other hand, extends the boundaries of an image by generating new content around the original picture.

The most prominent examples of such solutions are DALL-E and Photoshop’s Content-Aware Fill. They are usually used for image restoration, expanding the context of visuals, or filling gaps in photos.

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4. 3D Model and Object AI Generators

These tools create 3D models or objects that can be used in animations, games, or design projects. They often start with a 2D sketch or description and then create a 3D representation.

Such tools are: NVIDIA GauGAN, Mesh R-CNN, OpenAI’s Point-E. Most often, they are used in game development, 3D printing, and virtual reality content.

5. GAN-Based (Generative Adversarial Networks) AI Generators

Such tools use GANs: two neural networks (a generator and a discriminator) compete with each other to create realistic images. With their help, you can create very vivid, lifelike visuals in high resolutions.

The most prominent examples of these tools are StyleGAN and BigGAN. They are used to create realistic human faces, deepfake videos, artwork, and animation.

6. Neural Filters and Enhancement AI Generations

These tools don’t create visuals from scratch. Instead, they enhance or modify them by applying filters that can improve quality, add effects, or change facial expressions and features.

Examples of such tools are Adobe Photoshop, Neural Filters, and Luminar AI. They are often used for photo editing, retouching, and improving image quality.

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To Sum Up

AI image generators changed the way visuals are created and used these days. They offer an accessible, budget-friendly, and versatile solution for various content needs and can cater to different use cases, from creating hyper-realistic images to stylizing existing photos or generating 3D models. While traditional visual artists and designers remain crucial for their expertise and creativity, AI image generators can complement their skills and open up new possibilities for creative expression and practical applications.