Audience
Users that want to generate videos using AI
About Vidu
Vidu Studio AI is a text-to-video generator. Vidu Studio AI is capable of generating 16-second videos in 1080p resolution, and it is considered a competitor to OpenAI's Sora AI model. The model is known for its ability to simulate the physical world, maintain consistent characters, scenes, and timelines across the generated videos, and produce imaginative content.
Integrations
API:
Yes, Vidu offers API access
No integrations listed.
Company Information
Vidu
www.vidu.studio/
Videos and Screen Captures
Dream Machine
Dream Machine is an AI model that makes high quality, realistic videos fast from text and images.
It is a highly scalable and efficient transformer model trained directly on videos making it capable of generating physically accurate, consistent and eventful shots. Dream Machine is our first step towards building a universal imagination engine and it is available to everyone now!
Dream Machine is an incredibly fast video generator! 120 frames in 120s. Iterate faster, explore more ideas and dream bigger!
Dream Machine generates 5s shots with a realistic smooth motion, cinematography, and drama. Make lifeless into lively. Turn snapshots into stories.
Dream Machine understands how people, animals and objects interact with the physical world. This allows you to create videos with great character consistency and accurate physics.
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Flow Studio
Flow Studio generates fully-produced, film-quality 3-minute videos with engaging plots, consistent characters automatically matched background music and sound effects, and no need for post-production editing, all with a single click.
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VideoPoet
VideoPoet is a simple modeling method that can convert any autoregressive language model or large language model (LLM) into a high-quality video generator. It contains a few simple components. An autoregressive language model learns across video, image, audio, and text modalities to autoregressively predict the next video or audio token in the sequence. A mixture of multimodal generative learning objectives are introduced into the LLM training framework, including text-to-video, text-to-image, image-to-video, video frame continuation, video inpainting and outpainting, video stylization, and video-to-audio. Furthermore, such tasks can be composed together for additional zero-shot capabilities. This simple recipe shows that language models can synthesize and edit videos with a high degree of temporal consistency.
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Kling
Kling is a large model of video generation with strong video generation capabilities, allowing users to easily and efficiently complete art video creation. With a 3D time-space joint attention mechanism, it can better model complex time-space sports and generate video content of a larger movement, while being able to comply with the laws of motion. Thanks to efficient training infrastructure, extreme reasoning optimization, and scalable infrastructure, the model can generate video with a frame of 30 FPS for 2 minutes. Based on the self-research model architecture and the powerful modeling capabilities, Kling can simulate the physical characteristics of the real world and generate videos that conform to the laws of physics. Based on a deep understanding of the meaning of text-video, it can be translated into a user's rich imagination into a concrete picture, fictional scenes that will not appear in the real world.
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Product Details
Platforms Supported
SaaS
Training
Documentation
Videos
Support
Online