Image-to-Video (I2V)

Image-to-Video (I2V) is an AI generation workflow where a still image serves as the starting point for video creation. Rather than generating every visual element from scratch, the model analyzes the input image and predicts how the scene could naturally evolve over time.

LTX 2.3 preserves the most important characteristics of the source image—including composition, colors, characters, objects and overall style—while generating realistic motion between frames. Users can further guide the animation with text prompts that describe movement, camera behavior or the desired atmosphere.

Compared with Text-to-Video, Image-to-Video provides significantly greater visual control because the initial composition is already defined. This makes it one of the most widely used workflows for creators who need consistency between generated videos.

The Image-to-Video workflow begins with a reference image supplied by the user. LTX 2.3 analyzes its visual structure, identifies subjects, perspective, lighting, textures and composition before generating motion across subsequent frames.

An optional text prompt can further describe how the scene should evolve. For example, users can specify camera movements, environmental effects, subject actions or cinematic styles while the original image remains the visual anchor of the generation.

Because the model starts from an existing frame, Image-to-Video generally produces stronger visual consistency than generating an entirely new scene from text alone. This is particularly valuable when working with branded assets, illustrations, concept art or product photography.

Image-to-Video is commonly used in creative workflows where preserving the appearance of the original image is more important than generating an entirely new composition.

Typical applications include:

• animating digital artwork
• bringing illustrations to life
• product visualization
• marketing campaigns
• social media content
• character animation
• architectural visualization
• historical photo animation
• concept art presentation

Many creators also use Image-to-Video to prototype scenes before combining them with additional editing or video extension workflows.

Advantages

• Excellent visual consistency.
• Preserves composition and character identity.
• Greater creative control.
• Ideal for branded or commercial assets.
• Produces predictable results.

Limitations

• Animation quality depends on the input image.
• Low-quality images limit generation quality.
• Extreme motion may reduce consistency.
• Some scenes require multiple iterations for natural movement.

Using a clean, high-resolution source image almost always produces better results than relying on heavily compressed or low-quality inputs.

Successful Image-to-Video generation begins with selecting an image that provides the model with enough visual information.

Recommended practices include:

• use high-resolution images
• avoid heavy compression artifacts
• keep the main subject clearly visible
• describe camera movement separately from subject movement
• introduce motion gradually
• avoid unrealistic animation requests
• refine prompts through multiple iterations

For commercial projects, many creators first generate or prepare a high-quality key image before using Image-to-Video to produce consistent animations based on that visual foundation.