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What is ModelScope?

This advanced system employs a complex multi-stage diffusion model to translate English text descriptions into corresponding video outputs. It consists of three interlinked sub-networks: the first extracts features from the text, the second translates these features into a latent space for video, and the third transforms this latent representation into a final visual video format. With around 1.7 billion parameters, the model leverages the Unet3D architecture to facilitate effective video generation through a process of iterative denoising that starts with pure Gaussian noise. This cutting-edge methodology enables the production of engaging video sequences that faithfully embody the stories outlined in the input descriptions, showcasing the model's ability to capture intricate details and maintain narrative coherence throughout the video. Furthermore, this system opens new avenues for creative expression and storytelling in digital media.

What is DreamFusion?

Recent progress in text-to-image synthesis has been driven by diffusion models trained on vast collections of image-text pairs. To effectively adapt this approach for 3D synthesis, there is a critical need for large datasets of labeled 3D assets and efficient architectures capable of denoising 3D information, both of which are currently insufficient. This research aims to tackle these obstacles by utilizing an established 2D text-to-image diffusion model to facilitate text-to-3D synthesis. We introduce a groundbreaking loss function based on probability density distillation, enabling a 2D diffusion model to guide the optimization of a parametric image generator effectively. By applying this loss within a DeepDream-inspired framework, we enhance a randomly initialized 3D model, specifically a Neural Radiance Field (NeRF), through gradient descent, ensuring its 2D renderings from various angles demonstrate reduced loss. As a result, the generated 3D representation can be viewed from multiple viewpoints, illuminated under different lighting conditions, or integrated seamlessly into a variety of 3D environments. This innovative approach not only addresses existing limitations but also paves the way for the broader application of 3D modeling in both creative and commercial sectors, potentially transforming industries reliant on visual content.

Media

Media

Integrations Supported

01.AI
CodeQwen
GLM-4.5
Qwen 4
Qwen-7B
Qwen2
Qwen2-VL
Qwen2.5-1M
Qwen2.5-Coder
Qwen2.5-Max
Qwen3
Qwen3.6-27B
Qwen3.6-35B-A3B
Qwen3.6-Max-Preview
Qwen3.7-Max
Qwen3.7-Plus
Qwen3.8-27B
Qwen3.8-Flash-Next
Qwen3.8-Max
Qwen3.8-Omni-Flash

Integrations Supported

API Availability

API Availability

Pricing Information

Free
Free Version

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Not specified

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

Alibaba Cloud

Company Location

China

Company Website

modelscope.cn/

Company Facts

Organization Name

DreamFusion

Company Website

dreamfusion3d.github.io

Categories and Features

AI Gateways

Not specified

AI Inference

Not specified

AI Tools

Not specified

AI Video Generators

Not specified

ML Model Deployment

Not specified

Categories and Features

AI Tools

Not specified

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