How to Create AI Videos from Text and Images: A Practical Guide

AI video generation has become an increasingly practical way to turn creative ideas into visual content. Instead of relying entirely on traditional filming and editing, creators can now use AI models to generate video clips from text prompts, reference images, and other visual inputs.

However, getting a good result involves more than simply entering a prompt. Choosing the right workflow, preparing reference materials, and writing clear instructions can make a significant difference.

In this guide, we'll explore how AI video generation works and how to build a more effective workflow.

1. Understanding AI Video Generation

AI video generation uses machine learning models to create video content based on user-provided inputs.

The most common approaches include:

• Text-to-Video: Generate a video directly from a written description.
• Image-to-Video: Upload an image and use it as the starting point for an animated scene.
• Reference-Based Generation: Provide visual references to guide the appearance, style, or content of a generated video.
• First and Last Frame Generation: Define the beginning and ending frames to guide the transition between two visual states.

Each approach serves a different purpose. Text-to-video is useful for exploring creative concepts, while image and reference-based workflows offer more control over visual consistency.

2. How to Write Better AI Video Prompts

Prompt quality plays an important role in video generation.

A useful prompt should describe several elements:

Subject: What should appear in the video?

Action: What should the subject do?

Environment: Where does the scene take place?

Camera Movement: Should the camera pan, zoom, orbit, or remain stationary?

Visual Style: Should the output look cinematic, realistic, animated, or documentary-style?

For example:

"A white sports car driving along a coastal road at sunset, warm golden lighting, cinematic tracking shot, realistic reflections, smooth camera movement, detailed environment."

This provides the model with a clearer description than simply asking it to generate a car video.

3. Using Reference Images for Better Results

Text prompts are flexible, but they may not always preserve the exact appearance of a specific subject.

Reference images can help solve this problem.

For example, when creating a product video, you can provide a photograph of the product and describe the desired camera movement.

A practical workflow looks like this:

1. Prepare a clear reference image.
2. Upload it to an image-to-video or reference-based generation model.
3. Describe the movement and camera direction.
4. Specify which visual elements should remain unchanged.
5. Generate and review the result.

This approach is particularly useful for product demonstrations, marketing visuals, character animation, and creative storytelling.

4. Choosing the Right AI Video Generation Tool

Different AI models have different strengths. Some focus on text-to-video generation, while others provide more advanced reference-based workflows or synchronized audio.

One platform worth exploring is ZMS AI, an AI creation platform that brings different AI video and image generation models together.

Instead of limiting your workflow to one generation approach, you can explore different models and select an option that matches your creative requirements.

When evaluating an AI video tool, consider:

• Supported input types, including text and images.
• Video resolution and generation duration.
• Reference image capabilities.
• Camera movement and motion quality.
• Generation speed and credit consumption.
• Output consistency across multiple generations.

These factors are often more useful than choosing a tool based only on its advertised features.

5. A Practical Workflow for Creating AI Videos

Here is a simple workflow you can follow:

Step 1: Define Your Concept

Decide what you want to create. A product advertisement, cinematic scene, animated character, or short social media video will require different prompts and visual references.

Step 2: Prepare Your Inputs

Write a detailed prompt and collect any reference images that may help guide the generation process.

Step 3: Select a Suitable Model

Choose a model based on your requirements. For example, prioritize reference support when visual consistency is important.

Step 4: Generate the Video

Run the generation process and review the output. Pay attention to motion, subject consistency, camera movement, and unwanted visual artifacts.

Step 5: Refine Your Results

If the output does not match your expectations, adjust one or two prompt elements at a time rather than rewriting everything.

This makes it easier to understand which changes actually improve the result.

6. Final Thoughts

AI video generation is not simply about producing a video with one prompt. It is a process of combining creative direction, reference materials, model selection, and iterative refinement.

By understanding the differences between text-to-video, image-to-video, and reference-based generation, creators can build more predictable workflows and get better results.

If you want to explore different AI video generation approaches in one place, take a look at ZMS AI and experiment with the available creative tools.

The best way to understand what these models can do is to test them with your own ideas and compare the results.