Creating consistent images using artificial intelligence (AI) is the point where many projects stall or cannot continue due to the feeling of generative AI that cannot be controlled in detail. Since achieving consistency is essential to maintain visual coherence in projects that involve recurring characters, such as video games, graphic novels or animated series.
Below are some basic tips and techniques to ensure that AI-generated characters and scenes remain uniform and visually coherent.
1. Define a Clear and Concrete Visual Style
Selecting and defining a specific visual style is crucial for coherence. For example, 2D toon art or japanese anime style may be a popular choice due to its defined lines and vibrant colors. It is important to describe this style in each request so that the AI can replicate it accurately. By defining a clear visual style, a standard is set that the AI will follow, ensuring that all images share a uniform appearance.
2. Detailed Description and Uncommon Traits of Characters
The first step to achieving consistency in characters is to provide detailed descriptions that include physical traits, clothing, and other distinctive details. It is essential to specify physical characteristics such as eye color, hair type, height, and build. A basic tip is to include some unusual features of the character that allow them to be easily identified, such as fuchsia hair or an eye patch.
Example (ChatGPT 4o):
- Name: Vicky
- Physical Characteristics: Young Australian with vibrant brown eyes and shoulder-length, messy fuchsia hair.
- Clothing: Red T-shirt and a pearl blue bandana around the neck.
- Visual Style: 2D toon art.
3. Description of the Environment and Scene
When characters are part of a scene, it is crucial to describe the environment and any other relevant elements. Detailing the place where the characters are, the objects surrounding them, and the actions they are performing helps the AI create a more accurate and coherent image. The environment description should include details such as location, weather, lighting, and any decorative elements that might influence the appearance of the scene.
4. Multiple Characters
When multiple characters are included in a scene could be hard to get correctly, it is important to describe them separately to avoid the AI mixing their traits. Providing individual and detailed descriptions for each character ensures that the AI represents them correctly and maintains their distinctive characteristics. This is especially relevant in group scenes where the AI might confuse traits if they are not described clearly and separately.
Example (ChatGPT 4o):
- Name: Emma
- Physical Characteristics: Young blonde woman with vibrant blue eyes and long hair.
- Clothing: Yellow jacket and blue jeans.
- Name: Vicky
- Physical Characteristics: Young Australian with vibrant brown eyes and shoulder-length, messy fuchsia hair.
- Clothing: Red T-shirt and a pearl blue bandana around the neck.
- Scene Description: Vicky and Emma, eating ice cream, jumping, and feeding pigeons.
5. Maintain Consistency Across Multiple Images
To maintain consistency across multiple images, reusing detailed descriptions of characters and settings is an effective practice. Saving these descriptions and using them as a reference for each new image request ensures that all important details remain the same in each image. This approach not only saves time but also gets you closer to visual coherence throughout the entire project.
Conclusion
Achieving consistency in AI-generated images requires attention to detail and precise descriptions. Providing detailed descriptions of characters, including physical traits, clothing, and visual style, along with a clear description of the environment, ensures that the generated images are coherent and uniform. Applying these tips will help maintain a consistent and attractive visual narrative in any creative project.
These tips may vary depending on the LLM model being used, they may be basic for those with a lot of experience in the area, or they may be unnecessary for those who use tools like layer.ai or scenario.com, but for everyone else I hope this could be useful in your projects.
Putting these tips into practice, as well as other more advanced techniques, allows a video game generation project with Artificial Intelligence like Qwestar to be viable and exciting.
