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18 changes: 5 additions & 13 deletions README.md
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https://github.com/user-attachments/assets/5f599ad0-0922-414b-a8ab-e789da068efa


## 📋 TODO
## About EgoX

### 🔹 This Week
- [x] Release **inference code**
- [x] Release **model weights**
- [x] Release **data preprocessing code (for inference)**
**EgoX** is a novel egocentric video generation framework that produces first-person (ego-view) videos from a single third-person (exo-view) video input. By leveraging both exocentric observations and egocentric priors, EgoX enables realistic viewpoint transformation while preserving temporal consistency and scene structure. The method introduces a unified conditioning strategy that integrates spatial and channel-wise information within clean latent representations, requiring only lightweight LoRA-based adaptation. EgoX is built upon large-scale video diffusion models and is trained on the Ego-Exo4D dataset, making it a powerful tool for egocentric video synthesis and related research applications.

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### 🔹 By End of December
- [x] Release **training code**
- [x] Release **data preprocessing code (for train)**

### 🔹 Ongoing
- [ ] Release **user-friendly interface**

## 🛠️ Environment Setup

### System Requirements

- **GPU**: < 80GB (for inference) < 140GB (for train)
- **GPU**: 80GB VRAM (for inference), ≥ 140GB VRAM (for training)
- **CUDA**: 12.1 or higher
- **Python**: 3.10
- **PyTorch**: Compatible with CUDA 12.1
- **PyTorch**: Version compatible with CUDA 12.1


### Installation

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