Update README.md

README.md

@@ -9,4 +9,168 @@ tags:
 - RGBA
 - video
 - generation
----
+---
+
+<div align="center">
+
+  <h1>
+    <img src="assets/loopy-logo.apng" alt="Loopy logo" height="32" style="vertical-align: middle; margin-right: 8px;"/>
+    Loopy
+  </h1>
+
+  <h3>Seamless Video Loop Generation via Anchored Looping Shift of Positional Embedding</h3>
+
+[![arXiv](https://img.shields.io/badge/arXiv-XXXX.XXXXX-red)](https://arxiv.org/abs/XXXX.XXXXX)
+[![Project Page](https://img.shields.io/badge/Project_Page-Link-green)](https://donghaotian123.github.io/Loopy/)
+[![🤗 HuggingFace](https://img.shields.io/badge/%F0%9F%A4%97%20HuggingFace-Model-orange)](https://huggingface.co/htdong/Loopy)
+
+</div>
+
+<img src="assets/teaser.png" alt="Loopy Qualitative Results" style="max-width: 100%; height: auto;">
+
+>Our **Loopy** generates high-quality looping videos with seamless transitions at loop boundaries and diverse motion. It also supports RGBA with semi-transparent effects. In the application block, all elements—including game assets and Loopy character stickers—are generated by our **Loopy**.
+
+---
+
+### 🔥 News
+* **[2026.8.24]** Released Loopy, the Wan2.2-T2V-A14B–adapted weights and inference code are now open-sourced.
+* **[2026.8.24]** Our technical report is available on [arXiv](https://arxiv.org/abs/XXXX.XXXXX).
+
+---
+
+### 📝 To-Do List
+
+- [x] **Paper**: Release the technical report on arXiv.
+- [x] **Inference Code**: Released the looping inference pipeline for Loopy.
+- [x] **Model Weights**: Release the high-noise / low-noise LoRA checkpoints.
+
+---
+### 🌟 Showcase
+
+##### Seamless Looping Video Generation
+
+<!-- | Prompt | Preview Video | Alpha Video |
+| :---: | :---: | :---: |
+| "Medium shot. A little girl holds a bubble wand and blows out colorful bubbles that float and pop in the air. The background of this video is transparent. Realistic style." |
+  <div style="display: flex; gap: 10px;">
+    <img src="girl.gif" alt="..." style="flex: 1; min-width: 200px;">
+  </div> |
+  <div style="display: flex; gap: 10px;">
+    <img src="girl_pha.gif" alt="..." style="flex: 1; min-width: 200px;">
+  </div> | -->
+| Preview Video | Preview Video |
+| :---: | :---: |
+| <img src="assets/human.apng" width="320" height="180" style="object-fit:contain; display:block; margin:auto;"/> | <img src="assets/loopy-6.apng" width="320" height="180" style="object-fit:contain; display:block; margin:auto;"/> |
+
+##### For more results, please visit [Our Website](https://donghaotian123.github.io/Loopy/)
+
+### 🚀 Quick Start
+
+##### 1. Environment Setup
+
+```bash
+# Clone the project repository
+git clone https://github.com/WeChatCV/Loopy.git
+cd Loopy
+
+# Create and activate Conda environment
+conda create -n Loopy python=3.11 -y
+conda activate Loopy
+
+# Install dependencies
+pip install -r requirements.txt
+```
+
+##### 2. Model Download
+
+Download [Wan2.2-T2V-A14B](https://huggingface.co/Wan-AI/Wan2.2-T2V-A14B)
+
+Download the LightX2V 4-step distillation LoRAs for both experts:
+[high noise](https://huggingface.co/lightx2v/Wan2.2-Distill-Loras/blob/main/wan2.2_t2v_A14b_high_noise_lora_rank64_lightx2v_4step_1217.safetensors) /
+[low noise](https://huggingface.co/lightx2v/Wan2.2-Distill-Loras/blob/main/wan2.2_t2v_A14b_low_noise_lora_rank64_lightx2v_4step_1217.safetensors)
+
+Download [Loopy](https://huggingface.co/htdong/Loopy) (`high_noise.safetensors` and
+`low_noise.safetensors`)
+
+---
+
+### 🧪 Usage
+
+Write one prompt per line in a plain UTF-8 text file, then launch the batch inference:
+
+```bash
+output_path="./checkpoints"
+mkdir -p $output_path
+
+torchrun --nproc_per_node=8  generate_2.2_new.py --task t2v-A14B --size 832*480 \
+        --ckpt_dir Wan-AI/Wan2.2-T2V-A14B \
+        --dit_fsdp --t5_fsdp --ulysses_size 8 \
+        --frame_num 53 \
+        --sample_steps 4 \
+        --high_lightx2v_path "wan2.2_lora/wan2.2_t2v_A14b_high_noise_lora_rank64_lightx2v_4step_1217.safetensors" \
+        --low_lightx2v_path "wan2.2_lora/wan2.2_t2v_A14b_low_noise_lora_rank64_lightx2v_4step_1217.safetensors" \
+        --high_lora_path high_noise.safetensors \
+        --low_lora_path low_noise.safetensors \
+        --prompt_file prompt.txt \
+        --output_dir $output_path/results  2>&1 | tee -a $output_path/results.log
+
+```
+
+Or simply run the packaged script after editing the paths inside it:
+
+```bash
+bash test.sh
+```
+
+You can specify the weights of `Wan2.2-T2V-A14B` with `--ckpt_dir`, the LightX2V distillation
+LoRAs with `--high_lightx2v_path` / `--low_lightx2v_path`, and the Loopy LoRAs with
+`--high_lora_path` / `--low_lora_path`. Wan2.2-T2V-A14B is a two-expert MoE model, so the
+high-noise and low-noise branches each need their own pair of LoRAs.
+
+Generated videos are written to `--output_dir`, one subdirectory per prompt, each containing
+`fgr.mp4`.
+
+
+
+**Prompt Writing Tip:** Describe a subject whose motion is naturally periodic or continuous —
+falling snow, drifting clouds, flowing water, a walking animal, a rotating object. State the
+visual style and the shot type (close-up, medium shot, wide shot) as well. Prompts support
+both Chinese and English input.
+
+```bash
+# An example of prompt.
+An Arctic fox leaps nimbly through the snow while hunting, its white fur blending seamlessly with the snowflakes. Realistic style; a scene of winter wildlife.
+```
+
+---
+
+### 🤝 Acknowledgements
+
+This project is built upon the following excellent open-source projects:
+* [Wan2.2](https://github.com/Wan-Video/Wan2.2) (base video generation model)
+* [LightX2V](https://github.com/ModelTC/LightX2V) (inference acceleration)
+* [DiffSynth-Studio](https://github.com/modelscope/DiffSynth-Studio) (training/inference framework)
+
+We sincerely thank the authors and contributors of these projects.
+
+---
+
+### ✏️ Citation
+
+If you find our work helpful for your research, please consider citing our paper:
+
+```bibtex
+@article{haotiandong2026loopy,
+  title   = {Loopy: Seamless Video Loop Generation via Anchored Looping Shift of Positional Embedding},
+  author  = {Haotian Dong, Wenjing Wang, Chen Li, Jing Lyu, Xin Wang, Di Lin},
+  journal = {arXiv preprint},
+  year    = {2026}
+}
+```
+
+---
+
+### 📬 Contact Us
+
+If you have any questions or suggestions, feel free to reach out via
+[GitHub Issues](https://github.com/WeChatCV/Loopy/issues). We look forward to your feedback!