How can we make AI videos achieve a cinematic look? I’ve been constantly pursuing this. Since working with AI last year, I’ve only begun to gain a cinematic feel—there’s still much to learn and improve. A cinematic quality often gives people a sense of sophistication and aesthetic pleasure.
Color grading is the most effective way to achieve cinematic quality. For live-action filmmaking, it is an indispensable professional step. In AI filmmaking, color grading becomes even more important because we often use different image generation software and different video generation software during production, resulting in naturally inconsistent visual styles.
For example, some images are generated by Flux while others are from Midjourney – the former’s lighting effects are clearly inferior to the latter. The texture inconsistencies are even more pronounced with multimodal editing models like Doubao and Flux Kontext.
Color grading is the most effective method for making cross-software creations consistent. In AI filmmaking, we have at least two opportunities for color grading: once for images and once for videos. You can first apply high saturation to images, then low saturation to videos, controlling the final presentation effect.
Since we can color-grade images, we have significant room for manipulation. Video color grading requires more professional skills, while image color grading offers professional, user-friendly software options. Even filtering images can give your AI videos a distinctive tone.
The most important aspect of tone is consistency – whatever tone you adopt in your video should remain consistent throughout. Consistency is the foundation of art. The tone should first align with the story – for instance, a gloomy story might use a Gotham filter, while a sunny, bright story would use bright tones.
I usually employ dark tones because they more easily create a cinematic feel. Movie theaters are very dark environments, and human eyes are more comfortable viewing darker films. However, we’re now in the smartphone-viewing era, so you don’t necessarily need to follow this rule. For example, new Chinese-style color grading might be more suitable for the Chinese market.
The second way to achieve cinematic quality is to focus on shot variety. AI image generation software typically gives you front-facing medium shots. Now, with editing tools like Flux Kontext, don’t stick to front-facing medium shots – use high-angle and low-angle shots according to narrative needs.
The use of close-ups deserves particular attention. Many AI videos lack close-ups. While everyone knows to use wide shots to establish scenes, close-ups – which bring audiences emotionally closer to characters – are often overlooked. Close-up images can be well controlled with Flux, as Flux lacks in scenes but achieves good consistency with characters.
Creating multiple shot types with AI used to be very challenging. Now, you can use Dreamina 3.0’s multi-shot feature or image editing tools like Flux Kontext. In any case, more camera angles make films feel more expensive. Don’t overuse empty shots, but increase close-ups to compensate for AI’s many narrative shortcomings.
The third way to achieve cinematic quality is to give characters some imperfections. For example, battle damage or facial textures make everything look like it was shot with an IMAX camera. I usually apply at least two rounds of upscaling to characters, especially those in close-ups, to make them look less perfect.
Upscaling is an indispensable step. In AI videos, you can upscale both images and videos. If you want to upscale a screenshot from a video, you can use Supir. For general upscaling, you can use Magnific to add more details to the image.
You can skip many steps but don’t skip upscaling.
The fourth way to achieve cinematic quality is to provide enough “Eye Candy” – horizontal or vertical cutting of sufficient lines during camera movements. This is challenging to accomplish in AI videos, but carefully observe AI camera movements and identify shots with the most cutting lines. This brings us to camera movement, which should follow the rules of viewpoint positioning – it’s not necessarily about crazy first and last frames solving all problems.
The fifth point is attention to sound. Although I haven’t found excellent Chinese TTS software yet, ElevenLabs is excellent for English. Additionally, atmospheric soundtracks are essential – Suno 4.5 has impressive results. Film is an expression of audiovisual language; we must pay attention to audio after handling visuals. I usually use dark baroque-style film soundtracks because I’m a Bach fan.
These are the methods I’ve explored so far for creating cinematic AI videos, and I hope they help you. I’m also working hard to improve, ensuring my videos look more cinematic than the previous ones. So, I put great effort into maintaining consistency in tone, characters, and scenes.
Follow me as we explore AI filmmaking together.
