HuMo – A multimodal video generation framework jointly launched by Tsinghua University and ByteDance

What is HuMo？

HuMo is a multimodal video generation framework jointly developed by Tsinghua University and ByteDance Intelligent Creation Lab, with a focus on human-centric video generation. It can generate high-quality, fine-grained, and controllable human videos from multimodal inputs such as text, images, and audio. HuMo supports strong text-prompt following, consistent subject retention, and audio-driven motion synchronization. It enables video generation from text-image, text-audio, and text-image-audio combinations, giving users greater customization and control.

The HuMo model is open-sourced on Hugging Face, with detailed installation guides and preparation steps. It supports video generation at 480P and 720P resolution, with 720P offering higher quality. HuMo also provides configuration files to customize generation behavior and outputs, including length, resolution, and the balance of text, image, and audio inputs.

Main Features of HuMo

• Text-Image driven video generation: Combines text prompts with reference images to customize character appearance, clothing, makeup, props, and scenes for personalized video creation.

• Text-Audio driven video generation: Generates synchronized video from text and audio inputs alone, without requiring image references, offering greater creative freedom.

• Text-Image-Audio driven video generation: Integrates text, image, and audio guidance for the highest level of customization and control, producing high-quality videos.

• Multimodal synergy: Supports strong text-prompt adherence, subject consistency, and audio-driven motion synchronization, enabling coherent multimodal video generation.

• High-resolution video generation: Compatible with 480P and 720P outputs, with higher quality available at 720P, suitable for diverse application needs.

• Customizable configuration: Through the generate.yaml file, users can adjust video length, resolution, and the balance of text, image, and audio inputs for personalized results.

Technical Principles of HuMo

• Multimodal input synergy: HuMo processes text, image, and audio simultaneously. Text provides detailed descriptions and instructions, images define character appearance, and audio drives character movements and expressions, making the generated videos natural and vivid.

• Unified generation framework: The framework fuses multimodal conditions (text, image, audio) to generate human-centric videos. By integrating different modalities, it achieves richer and more precise video generation than single-modality approaches.

• Powerful text-following capability: HuMo can accurately follow text prompts, translating descriptions into visual elements in the video. This enables users to control video content and style with detailed textual input.

• Consistent subject retention: Throughout video generation, HuMo maintains subject consistency, ensuring that character appearance and features remain stable across frames, avoiding inconsistencies common in generative models.

• Audio-driven motion synchronization: Audio input drives background sound, movements, and facial expressions. For example, characters can react to rhythm and tone in the audio, making videos more dynamic and lifelike.

• High-quality dataset training: HuMo is trained on high-quality datasets containing rich text, image, and audio samples, which help the model learn cross-modal relationships for better video quality.

• Customizable generation settings: Through configuration files, users can adjust parameters such as frame count, resolution, and the weighting of text and audio guidance, making the framework adaptable to different applications and needs.

Project Links for HuMo

• Official Website: https://phantom-video.github.io/HuMo/

• Hugging Face Model Hub: https://huggingface.co/bytedance-research/HuMo

• arXiv Paper: https://arxiv.org/pdf/2509.08519

Application Scenarios of HuMo

• Content creation: Generate high-quality videos for animation, advertising, short videos, and more, helping creators quickly realize creative concepts.

• Virtual and augmented reality: Build immersive virtual environments for more realistic and engaging user experiences.

• Education and training: Produce educational videos with vivid animations and audio explanations to improve comprehension of complex concepts.

• Entertainment and gaming: Generate character animations for games or create personalized virtual characters for entertainment applications.

• Social media: Create personalized, engaging video content for social platforms to increase user engagement.

• Advertising and marketing: Produce customized promotional videos tailored to target audiences, enhancing advertising effectiveness.