init

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+assets/teaser.png filter=lfs diff=lfs merge=lfs -text

.gitignore

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+*.safetensors
+*.pt

HuMo-17B/README_safetensors_shards.txt

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+This directory contains sharded safetensors converted from a PyTorch checkpoint.
+- Prefix: humo
+- Number of shards: 7
+- Max shard size: 10.00 GB
+- Total tensor bytes: 63.538 GB
+- Index file: humo.safetensors.index.json
+Each entry in weight_map maps a tensor name to the shard filename that contains it.

LICENSE

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README.md

@@ -1,3 +1,127 @@
----
-license: apache-2.0
----
+# HuMo: Human-Centric Video Generation via Collaborative Multi-Modal Conditioning
+
+<div align="center">
+  
+[![arXiv](https://img.shields.io/badge/arXiv%20paper-2502.11079-b31b1b.svg)](https://arxiv.org/abs/xxx)&nbsp;
+[![project page](https://img.shields.io/badge/Project_page-More_visualizations-green)](https://phantom-video.github.io/HuMo/)&nbsp;
+<a href="https://huggingface.co/bytedance-research/HuMo"><img src="https://img.shields.io/static/v1?label=%F0%9F%A4%97%20Hugging%20Face&message=Model&color=orange"></a>
+</div>
+
+
+> [**HuMo: Human-Centric Video Generation via Collaborative Multi-Modal Conditioning**](https://arxiv.org/abs/2509.08519)<br>
+> [Liyang Chen](https://scholar.google.com.hk/citations?user=jk6jWXgAAAAJ&hl)<sup> * </sup>, [Tianxiang Ma](https://tianxiangma.github.io/)<sup> * </sup>, [Jiawei Liu](https://scholar.google.com/citations?user=X21Fz-EAAAAJ), [Bingchuan Li](https://scholar.google.com/citations?user=ac5Se6QAAAAJ)<sup>&dagger;</sup>, [Zhuowei Chen](https://scholar.google.com/citations?user=ow1jGJkAAAAJ), [Lijie Liu](https://liulj13.github.io/), [Xu He](https://scholar.google.com.hk/citations?user=KMrFk2MAAAAJ&hl), [Gen Li](https://scholar.google.com/citations?user=wqA7EIoAAAAJ), [Qian He](https://scholar.google.com/citations?user=9rWWCgUAAAAJ), [Zhiyong Wu](https://scholar.google.com.hk/citations?hl=zh-CN&user=7Xl6KdkAAAAJ&)<sup> § </sup>
+> <br><sup> * </sup>Equal contribution,<sup> &dagger; </sup>Project lead, <sup> § </sup>Corresponding author
+> <br>Tsinghua University | Intelligent Creation Team, ByteDance<br>
+
+<p align="center">
+<img src="assets/teaser.png" width=95%>
+<p>
+
+## ✨ Key Features
+HuMo is a unified, human-centric video generation framework designed to produce high-quality, fine-grained, and controllable human videos from multimodal inputs—including text, images, and audio. It supports strong text prompt following, consistent subject preservation, synchronized audio-driven motion.
+
+> - **​​VideoGen from Text-Image**​​ - Customize character appearance, clothing, makeup, props, and scenes using text prompts combined with reference images.
+> - **​​VideoGen from Text-Audio**​​ - Generate audio-synchronized videos solely from text and audio inputs, removing the need for image references and enabling greater creative freedom.
+> - **​​VideoGen from Text-Image-Audio**​​ - Achieve the higher level of customization and control by combining text, image, and audio guidance.
+
+## 📑 Todo List
+- [x] Release Paper
+- [x] Checkpoint of HuMo-17B
+- [x] Inference Codes
+  - [ ] Text-Image Input
+  - [x] Text-Audio Input
+  - [x] Text-Image-Audio Input
+- [x] Multi-GPU Inference
+- [ ] Release Prompts to Generate Demo of ***Faceless Thrones***
+- [ ] HuMo-1.7B
+
+## ⚡️ Quickstart
+
+### Installation
+```
+conda create -n humo python=3.11
+conda activate humo
+pip install torch==2.5.1 torchvision==0.20.1 torchaudio==2.5.1 --index-url https://download.pytorch.org/whl/cu124
+pip install flash_attn==2.6.3
+pip install -r requirements.txt
+conda install -c conda-forge ffmpeg
+```
+
+### Model Preparation
+| Models       | Download Link                                                                                                                                           |    Notes                      |
+|--------------|---------------------------------------------------------------------------------------------------------------------------------------------------------|-------------------------------|
+| HuMo-17B      | 🤗 [Huggingface](https://huggingface.co/bytedance-research/HuMo/tree/main)   | Released before September 15
+| HuMo-1.7B | 🤗 [Huggingface](https://huggingface.co/bytedance-research/HuMo/tree/main) | To be released soon
+| Wan-2.1 | 🤗 [Huggingface](https://huggingface.co/Wan-AI/Wan2.1-T2V-1.3B) | VAE & Text encoder
+| Whisper-large-v3 |      🤗 [Huggingface](https://huggingface.co/openai/whisper-large-v3)          | Audio encoder
+| Audio separator |      🤗 [Huggingface](https://huggingface.co/huangjackson/Kim_Vocal_2)          | Remove background noise (optional)
+
+Download models using huggingface-cli:
+``` sh
+huggingface-cli download Wan-AI/Wan2.1-T2V-1.3B --local-dir ./weights/Wan2.1-T2V-1.3B
+huggingface-cli download bytedance-research/HuMo --local-dir ./weights/HuMo
+huggingface-cli download openai/whisper-large-v3 --local-dir ./weights/whisper-large-v3
+huggingface-cli download huangjackson/Kim_Vocal_2 --local-dir ./weights/audio_separator
+```
+
+### Run Multimodal-Condition-to-Video Generation
+
+Our model is compatible with both 480P and 720P resolutions. 720P inference will achieve much better quality.
+> Some tips
+> - Please prepare your text, reference images and audio as described in [test_case.json](./examples/test_case.json).
+> - We support Multi-GPU inference using FSDP + Sequence Parallel.
+> - ​The model is trained on 97-frame videos at 25 FPS. Generating video longer than 97 frames may degrade the performance. We will provide a new checkpoint for longer generation.
+
+#### Configure HuMo
+
+HuMo’s behavior and output can be customized by modifying [generate.yaml](humo/configs/inference/generate.yaml) configuration file.  
+The following parameters control generation length, video resolution, and how text, image, and audio inputs are balanced:
+
+```yaml
+generation:
+  frames: <int>                 # Number of frames for the generated video.
+  scale_a: <float>              # Strength of audio guidance. Higher = better audio-motion sync.
+  scale_t: <float>              # Strength of text guidance. Higher = better adherence to text prompts.
+  mode: "TA"                    # Input mode: "TA" for text+audio; "TIA" for text+image+audio.
+  height: 720                   # Video height (e.g., 720 or 480).
+  width: 1280                   # Video width (e.g., 1280 or 832).
+
+diffusion:
+  timesteps:
+    sampling:
+      steps: 50                 # Number of denoising steps. Lower (30–40) = faster generation.
+```
+
+#### 1. Text-Audio Input
+
+``` sh
+bash infer_ta.sh
+```
+
+#### 2. Text-Image-Audio Input
+
+``` sh
+bash infer_tia.sh
+```
+
+## Acknowledgements
+Our work builds upon and is greatly inspired by several outstanding open-source projects, including [Phantom](https://github.com/Phantom-video/Phantom), [SeedVR](https://github.com/IceClear/SeedVR?tab=readme-ov-file), [MEMO](https://github.com/memoavatar/memo), [Hallo3](https://github.com/fudan-generative-vision/hallo3), [OpenHumanVid](https://github.com/fudan-generative-vision/OpenHumanVid), and [Whisper](https://github.com/openai/whisper). We sincerely thank the authors and contributors of these projects for generously sharing their excellent codes and ideas.
+
+## ⭐ Citation
+
+If HuMo is helpful, please help to ⭐ the repo.
+
+If you find this project useful for your research, please consider citing our [paper](https://arxiv.org/abs/2502.11079).
+
+### BibTeX
+```bibtex
+@article{chen2025HuMo,
+  title={Human-Centric Video Generation via Collaborative Multi-Modal Conditioning},
+  author={Chen, Liyang and Ma, Tianxiang and Liu, Jiawei and Li, Bingchuan and Chen, Zhuowei and Liu, Lijie and He, Xu and Li, Gen and He, Qian and Wu, Zhiyong},
+  journal={arXiv preprint arXiv:2502.11079},
+  year={2025}
+}
+```
+
+## 📧 Contact
+If you have any comments or questions regarding this open-source project, please open a new issue or contact [Liyang Chen](lyangchen@outlook.com).

config.json

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+{
+    "_diffusers_version": "0.30.1",
+    "_HuMo_version": "1.0"
+}

requirements.txt

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+opencv-python>=4.9.0.80
+diffusers>=0.31.0
+transformers>=4.49.0
+tokenizers>=0.20.3
+accelerate>=1.1.1
+tqdm
+imageio
+easydict
+ftfy
+dashscope
+imageio-ffmpeg
+gradio>=5.0.0
+numpy>=1.23.5,<2
+xfuser>=0.4.1
+audio-separator==0.24.1
+moviepy==1.0.3
+onnxruntime-gpu
+mediapipe==0.10.18