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Average Ratings 0 Ratings

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ease
features
design
support

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Write a Review

Description

HunyuanVideo-Avatar allows for the transformation of any avatar images into high-dynamic, emotion-responsive videos by utilizing straightforward audio inputs. This innovative model is based on a multimodal diffusion transformer (MM-DiT) architecture, enabling the creation of lively, emotion-controllable dialogue videos featuring multiple characters. It can process various styles of avatars, including photorealistic, cartoonish, 3D-rendered, and anthropomorphic designs, accommodating different sizes from close-up portraits to full-body representations. Additionally, it includes a character image injection module that maintains character consistency while facilitating dynamic movements. An Audio Emotion Module (AEM) extracts emotional nuances from a source image, allowing for precise emotional control within the produced video content. Moreover, the Face-Aware Audio Adapter (FAA) isolates audio effects to distinct facial regions through latent-level masking, which supports independent audio-driven animations in scenarios involving multiple characters, enhancing the overall experience of storytelling through animated avatars. This comprehensive approach ensures that creators can craft richly animated narratives that resonate emotionally with audiences.

Description

This system utilizes a sophisticated multi-stage diffusion model for converting text descriptions into corresponding video content, exclusively processing input in English. The framework is composed of three interconnected sub-networks: one for extracting text features, another for transforming these features into a video latent space, and a final network that converts the latent representation into a visual video format. With approximately 1.7 billion parameters, this model is designed to harness the capabilities of the Unet3D architecture, enabling effective video generation through an iterative denoising method that begins with pure Gaussian noise. This innovative approach allows for the creation of dynamic video sequences that accurately reflect the narratives provided in the input descriptions.

API Access

Has API Yes 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

CodeQwen No 
Gradio Yes 
Qwen No 
Qwen 4 No 
Qwen2 No 
Qwen2-VL No 
Qwen2.5-1M No 
Qwen2.5-Coder No 
Qwen2.5-Max No 
Qwen2.5-VL No 
Qwen3 No 
Qwen3.6-27B No 
Qwen3.6-35B-A3B No 
Qwen3.7-Plus No 
Qwen3.8-27B No 
Qwen3.8-Flash-Next No 
Qwen3.8-Omni-Flash No 
Step 3.5 Flash No 
Step 5 Preview No 
Yi-Large No 

Integrations

CodeQwen Yes 
Gradio No 
Qwen Yes 
Qwen 4 Yes 
Qwen2 Yes 
Qwen2-VL Yes 
Qwen2.5-1M Yes 
Qwen2.5-Coder Yes 
Qwen2.5-Max Yes 
Qwen2.5-VL Yes 
Qwen3 Yes 
Qwen3.6-27B Yes 
Qwen3.6-35B-A3B Yes 
Qwen3.7-Plus Yes 
Qwen3.8-27B Yes 
Qwen3.8-Flash-Next Yes 
Qwen3.8-Omni-Flash Yes 
Step 3.5 Flash Yes 
Step 5 Preview Yes 
Yi-Large Yes 

Pricing Details

Free
Free Trial No 
Free Version Yes 

Pricing Details

Free
Free Trial No 
Free Version Yes 

Deployment

Web-Based No 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux Yes 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Tencent-Hunyuan

Country

United States

Website

github.com/Tencent-Hunyuan/HunyuanVideo-Avatar

Vendor Details

Company Name

Alibaba Cloud

Country

China

Website

modelscope.cn/

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