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wykup316/OmniCamera
OmniCamera is a image-to-video model from wykup316. Use it for the image-to-video task on the model card, and read the license before you ship it in a product.
OmniCamera: A Unified Framework for Multi-task Video Generation with Arbitrary Camera Control
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Updated Sep 3, 2026
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From the Hugging Face model README
OmniCamera: A Unified Framework for Multi-task Video Generation with Arbitrary Camera Control
OmniCamera is a unified camera-controllable video generation framework built on Wan2.2-TI2V-5B. It separates camera control from content conditioning and supports arbitrary pairings of three camera conditions and three content conditions.
| Camera condition | Text content | Image content | Video content |
|---|---|---|---|
| Camera-motion text | T2V | I2V | V2V |
| Explicit 3D trajectory | T2V | I2V | V2V |
| Reference motion video | T2V | I2V | V2V |
joint_params_step61000.pth is a partial full-finetuning checkpoint, not a
LoRA adapter and not a standalone copy of Wan2.2-TI2V-5B.
It contains BF16 parameters for:
The unchanged text encoder, VAE, tokenizer, and remaining DiT parameters must be
loaded from Wan-AI/Wan2.2-TI2V-5B.
cam_encoder: Linear(12, 3072) and
projector: Linear(3072, 3072) in blocks 0, 5, 10, 15, 20, and 25.dit. prefix from checkpoint keys.The original training/inference configuration uses:
3.0;704 x 1248;41;16 FPS;40;5.0.An end-to-end inference entry point and Hugging Face Space are being prepared.
The base model is distributed under the Apache 2.0 license. The license for this OmniCamera checkpoint will be finalized before the public release. This private repository is currently intended for deployment validation.
@article{wang2026omnicamera,
title = {OmniCamera: A Unified Framework for Multi-task Video Generation with Arbitrary Camera Control},
author = {Wang, Yukun and Li, Ruihuang and Tao, Jiale and Yang, Shiyuan and Chen, Liyi and Yang, Zhantao and Handz and Guo, Yulan and Shao, Shuai and Lu, Qinglin},
journal = {arXiv preprint arXiv:2604.06010},
year = {2026}
}