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Standards for Video Modeling

This week, I had a productive discussion with friends about the rapidly evolving world of video modeling technology and recorded some key insights.

Before Kling entered the market, tools like Runway and Pika were leading the way. While these products have made significant strides in video creation, there is still room to improve their usability.

For example, Runway offers extensive customization through manual controls for motion and camera settings. However, this can be challenging, especially for users who aren’t experts, sometimes leading to inconsistent results. Pika, with its unique parameter settings, also struggles to maintain image clarity during the transition from image to video, indicating that there’s always room for refinement.

Kling, developed by Kuaishou (a company where I previously worked), has made notable progress in addressing these usability challenges. My experience at Kuaishou, where I served as the product lead for a platform with over 10 million daily video uploads, has given me a unique perspective on Kling’s development.

Kling stands out because it’s been trained on extensive video datasets, which has significantly improved its ability to control motion, particularly in mimicking real-world movements. Unlike some other tools that rely on random generation, Kling is known for its consistency and reliability, making it a strong choice for creators.

Standards and Applications for Video Models

When evaluating video models, I focus on three primary aspects: technology, interaction, and visual quality. Based on my experience at Kuaishou and my current work at Pixfun, these criteria are essential for understanding where new video models excel and where they might need more development. Additionally, different models with varying scores are best suited for different applications:

60 Points: Basic functionality. Models should at least achieve 1080P resolution, maintain continuity in 3-5 second clips, accurately simulate physical movements, render scenes and elements with precision, and offer basic camera controls. This level of functionality is ideal for short video content, such as quick tutorials on TikTok or brief product demonstrations.

70 Points: Better control over visual details. Models that remain stable with longer clips, offer more control over motion, support custom trajectories for visual elements, allow extensive camera sweeps, and provide detailed rendering of features like facial expressions. This level is particularly suitable for content creators who need more detailed control in storytelling and branding. Such models could be used for YouTube tutorials or promotional videos where detail and visual consistency are crucial.

80 Points: Higher demands for motion and aesthetics. Models capable of generating 4K ultra-high-definition content with flexible camera angle control are expected at this stage. They should support editing and replacing video elements, accurately depict multi-character scenes, and represent complex artistic styles such as sci-fi. This level is essential for professional content creators, especially in the film and advertising industries, where high-quality visuals and complex animations are critical. Such models could be applied to short films or high-end brand advertisements requiring intricate visual effects and artistic expression.

90 Points: Cinematic-level quality and control. Models at this level should deliver 8K resolution, manage complex multi-character motions, precisely control facial expressions, integrate dynamic lighting effects, and customizable color schemes, and accurately depict culturally rich artistic styles, such as traditional Chinese art. This level of detail and control is necessary for models to be considered on par with traditional film production standards. Such models could be used for high-end film production or large-scale advertising campaigns that require top-tier aesthetic quality and visual control.

Pixfun’s Goal

As the former product lead responsible for managing a video platform with over 10 million daily uploads at Kuaishou, I have seen firsthand the challenges and opportunities in content creation. Now, as the founder of Pixfun, I’m excited to bring my experience into the AI industry.

At Pixfun, our goal is to help creators produce high-quality animated content while lowering the learning curve. We want to make it easier for anyone to create amazing animations without needing to master complex tools. By making advanced AI accessible and easy to use, we hope to drive the animation industry forward and empower creators everywhere.

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