At a time when generative AI is developing rapidly, video generation technology is becoming a new battlefield for major technology companies to compete. After OpenAI's Sora triggered a global buzz, domestic vendors have also launched their own AI video generation solutions. Recently, Baidu's commercial R&D team released a large model of multimodal generationMuseSteamerThis product not only won the world's first place in the overseas authoritative evaluation list of VBench, but also realized the synchronous generation of audio and video in the Chinese context for the first time.
Anatomy of MuseSteamer's Core Technical Capabilities
Powerful Chinese semantic understanding
The most prominent feature of MuseSteamer is its deep optimization for Chinese context. By building a billion-scale video slice database and adopting a three-stage data optimization system of "filtering-purifying-matching", it ensures precise semantic alignment between text instructions and visual elements. This targeted data processing allows the model to accurately understand the nuances and cultural connotations of Chinese cues.
Refined video structure description system
Unlike mainstream products in the industry, MuseSteamer adopts a structured video description method, which not only contains picture details (subject, background, motion, atmosphere, light and shadow), but also deeply integrates professional elements such as lens language, subject motion intensity, and style description. This refined description system covers a wide range of style types such as realistic, cinematic, cyberpunk, vintage film, minimalist, and anime.
Audio-video integration generates breakthroughs
One of the major innovations of MuseSteamer is the realization of real synchronous generation of audio and video. Through multimodal scheduling and audio/video integration learning model, the system can automatically deal with the three core issues of "who is talking, how to talk, and in what environment", so that multi-track audio such as dialogues, background sounds, music, etc. are naturally fused with the visual content, which greatly enhances the immersive degree of the viewer's experience.
Comprehensive product matrix to meet different needs
MuseSteamer offers a complete matrix of product versions that accurately cover the diverse needs of individual creators to professional film and television organizations:
Practical tests: capabilities and limitations at the same time
Outstanding performance in semantic understanding
In the semantic comprehension test, MuseSteamer showed impressive performance. For example, in the playground in the evening, a high school boy jumps up to shoot a basketball, and his figure is stretched out by the setting sun", the model accurately reproduces the complete flow of the jumping and shooting action, and the shadow of the character is consistent with the action, and the effect of the setting sun's light and shadow is natural and realistic. MuseSteamer shows a stronger semantic parsing ability than similar products in terms of deviation in action understanding.
The continuity of the action is noteworthy
In the test of "a rabbit tapping on the keyboard, then it picks up a cup to drink with one hand and continues to tap on the keyboard with the other hand", MuseSteamer not only completes the basic action sequence, but also independently adds rich facial expressions and micro-movements to the character, which makes the static graphic character vivid and lively. Although the action chain is slightly incomplete, the overall consistency is satisfactory.
Excellent performance in style control
In the fantasy style test, MuseSteamer accurately reproduced the description of the scene, "In fantasy style, a little girl runs forward on a shining unicorn through a valley of colorful bubbles". The resulting video is filled with a soft halo of light, colorful bubbles, starlight, fluttering skirts and other detailed elements, and the overall style is unified and coordinated.
Lens movement capability needs to be improved
However, MuseSteamer reveals obvious shortcomings when it comes to complex camera movements. In the "camera around the bat detective" test, the model almost did not realize the effective movement of the camera, which may be the technical limitations of the current version. Although the relatively simple "Lens Distance" command can be basically accomplished, the edges of the screen will show obvious stitching flaws.
Generation efficiency still needs to be optimized
From the overall test experience, MuseSteamer's generation speed is relatively slow, generally taking 3-5 minutes, which may affect the smoothness of the workflow for users who need to iterate their creations quickly.
The Future Picture of AI Video Generation
The release of MuseSteamer signifies that domestic AI video generation technology is rapidly catching up with the international advanced level. Although there is still room for improvement in certain complex scenarios, its breakthroughs in Chinese semantic understanding, style control and audio/video synchronization have set a new benchmark for the industry.
With the official release of the audible version in August and the successive launch of the Pro and Lite versions, MuseSteamer is expected to build an AI video generation ecology that covers the whole scene. For content creators, this not only means the upgrading of creative tools, but also represents a fundamental change in the way of creative expression.
The Turbo version of MuseSteamer is currently available for free on the "EYE" platform, interested users can visit huixiang.baidu.com Experience this revolutionary AI video generation technology for yourself.
