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HunyuanCustom

Paid

A Multimodal-Driven Architecture for Customized Video Generation

4.5
Inputs: text, image, audio, videoOutputs: video
Type
Saas
Company
Tencent

About HunyuanCustom

HunyuanCustom is a multimodal-driven architecture for customized video generation developed by Tencent, built upon the HunyuanVideo framework. It emphasizes subject consistency while supporting flexible user-defined conditions across multiple input modalities, including text, images, audio, and video. The framework introduces an image-text fusion module based on LLaVA for enhanced multimodal understanding, an image ID enhancement module that uses temporal concatenation to reinforce identity features across frames, an AudioNet module for hierarchical audio condition injection via spatial cross-attention, and a video-driven injection module that integrates latent-compressed conditional video through a patchify-based feature-alignment network. Extensive experiments demonstrate significant improvements over state-of-the-art open- and closed-source methods in terms of identity consistency, realism, and text-video alignment, and the system shows robustness in downstream tasks such as audio- and video-driven customized video generation.

Key Features

Multimodal conditioning: accepts text, image, audio, and video inputs
Subject identity consistency across video frames via temporal concatenation
Image-text fusion module based on LLaVA for enhanced multimodal understanding
Image ID enhancement module leveraging temporal concatenation to reinforce identity features
AudioNet module for hierarchical audio condition injection via spatial cross-attention
Video-driven injection module using patchify-based feature-alignment network
Built upon the HunyuanVideo generation framework
Supports single-subject and multi-subject video customization
Enables decoupled control over image, audio, and video conditions
Outperforms open-source and closed-source SOTA methods in ID consistency, realism, and text-video alignment

Pros & Cons

Pros
  • State-of-the-art identity consistency and realism in generated videos
  • Supports multiple input modalities (text, image, audio, video) for flexible control
  • Strong identity preservation across frames even for complex motions
  • Outperforms both open-source and closed-source methods in benchmarks
  • Enables controllable generation for various downstream tasks
Cons
  • Requires substantial computational resources (high-end GPUs) for inference
  • Currently a research prototype, not a commercial product with no easy-to-use interface
  • May have limited accessibility as it is not packaged as a turnkey SaaS tool
  • Dependence on HunyuanVideo framework may limit standalone adoption

Best For

Single-subject video customization with consistent identity (e.g., a person performing actions)Story generation with consistent characters across scenesAudio-driven customized video generation where audio conditions guide subject behaviorVideo-driven customized video generation using reference video as conditionMulti-subject video generation with identity preservation for each subject

Alternatives to HunyuanCustom

FAQ

What is HunyuanCustom?
HunyuanCustom is a multimodal customized video generation framework developed by Tencent that ensures subject consistency across text, image, audio, and video conditions.
What input modalities does HunyuanCustom support?
It supports text, image, audio, and video inputs for conditioned generation.
How does HunyuanCustom maintain identity consistency?
It uses an image ID enhancement module that concatenates image information along the temporal axis, leveraging the video model's temporal modeling ability to enhance subject identity across frames.
Is HunyuanCustom open source?
Yes, the project page provides links to GitHub and Hugging Face, indicating the model and code are available.
How does HunyuanCustom handle audio conditions?
It introduces an AudioNet module that achieves hierarchical alignment via spatial cross-attention to inject audio conditions.