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Video model

Video model transforms input text into dynamic video, endowing words with visual impact and expanding the dimensions of expression. It not only aids creators in saving considerable time but also generates high-quality, creative visual content. The potential of text-to-video models is fully showcased across various domains, including education, advertising, and entertainment.

The following model is available for purchase：

  • MaaS_KL
  • MaaS_HL
  • MaaS Haiper Video

MaaS_KL

The MaaS_KL series of text - to - video is a new - generation multi - modal video - generation large model. Through algorithm architecture innovation and full - stack optimization technology, it has achieved high - quality, high - efficiency, and highly controllable video content generation capabilities, providing revolutionary tools for fields such as film and television production, advertising and marketing, education, and entertainment.

  • Exceptional Video Generation Capabilities

It supports text - to - video and image - to - video functions, and also has a video continuation function. It can provide convenient video extensions for generated videos, offering more flexible creative methods for creators and facilitating the construction of complete video stories.

  • Generation of Large - scale and Reasonable Movements

By adopting a 3D spatio - temporal joint attention mechanism, it can better model complex spatio - temporal movements in videos. It can not only generate large - scale movements but also ensure that the generated movements are more in line with objective motion laws, allowing imagination to vividly unfold on the basis of realistic motion logic.

  • Simulation of Physical World Characteristics

It constructs an imaginary space that infinitely approximates reality and generates videos that conform to physical laws. By integrating a physical simulation engine and optical flow - guided frame interpolation technology, it achieves realistic rendering of dynamic effects such as smoke and fluids, enhancing the sense of reality and immersion of the video.

MaaS_HL

The MaaS_HL series of generative video models is an intelligent video generation solution based on deep learning technology. Through multi-modal input parsing and spatio-temporal consistency modeling, it realizes end-to-end generation from text/images to high-quality videos. This model adopts an innovative multi-frame consistency algorithm, combined with a professional camera movement special effects library, and supports core functions such as text-to-video, image-to-video, and subject stability control. It can be widely applied in scenarios such as content creation, advertising production, and virtual live streaming.

  • Powerful Multi-modal Generation Capability

It supports dual-modal inputs of text-to-video (T2V) and image-to-video (I2V). Whether it is constructing a virtual scene based on detailed text or extending a dynamic plot relying on a single image, it can accurately grasp the user's intention and efficiently produce video content, meeting diverse creative needs.

  • Excellent Subject Consistency Guarantee

With the unique "subject reference" technology, only one reference image is needed to construct a three-dimensional feature space. Under harsh scenarios such as complex lighting and multi-angle camera movements, third-party tests show that the facial feature restoration accuracy rate is as high as 98.7%, far exceeding the industry average, effectively overcoming the industry problem of unstable subject images.

  • Intelligent User Experience Optimization

It has a built-in AI prompt word generator that can automatically analyze user inputs and provide optimization suggestions, greatly improving the accuracy rate of novice creators in following instructions and reducing the creative threshold. At the same time, the single-round generation time is controlled within 1 - 3 minutes, and it supports 5 parallel tasks. Combined with the multi-frame consistency algorithm, while ensuring high-quality output, the generation cost is significantly reduced.

MaaS Haiper Video

MaaS Haiper Video leverages deep learning technology to generate high-quality video content based on given text descriptions or specific instructions. It comprehends the input text and translates it into vivid video sequences, encompassing image generation, dynamic effects addition, and scene construction.

  • Powerful Generation Capabilities

    It can produce diverse videos based on various text inputs, covering a wide range of themes and styles. Whether it's landscape descriptions, storytelling, or expression of abstract concepts, the model can transform them into visually compelling videos.

  • High-Quality Video Generation

    The generated video sequences possess high clarity and realism. It can simulate real-world lighting, materials, and textures, making the videos appear more natural and lively.

  • Flexibility and Customizability

    Users can adjust the model's parameters and input text descriptions to control aspects such as video duration and resolution, catering to different needs and application scenarios.