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README.md

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-# [ICCV'25] TARO: Timestep-Adaptive Representation Alignment with Onset-Aware Conditioning for Synchronized Video-to-Audio Synthesis
-<br>
-
-**[Tri Ton](https://triton99.github.io/)<sup>1</sup>, [Ji Woo Hong](https://jiwoohong93.github.io/)<sup>1</sup>, [Chang D. Yoo](https://sanctusfactory.com/family.php)<sup>1†</sup>** 
-<br>
-<sup>1</sup>KAIST, South Korea
-<br>
-†Corresponding authors
-
-<p align="center">
-        <a href="https://triton99.github.io/taro-site/" target='_blank'>
-        <img src="https://img.shields.io/badge/🐳-Project%20Page-blue">
-        </a>
-        <a href="https://arxiv.org/abs/2504.05684" target='_blank'>
-        <img src="https://img.shields.io/badge/arXiv-2312.13528-b31b1b.svg">
-        </a>
-        <img alt="GitHub Repo stars" src="https://img.shields.io/github/stars/triton99/TARO">
-</p>
-
-## 📣 News
-- **[09/2025]**: Training & Inference code released.
-- **[06/2025]**: TARO accepted to ICCV 2025 🎉.
-- **[04/2024]**: Paper uploaded to arXiv. Check out the manuscript [here](https://arxiv.org/abs/2504.05684).(https://arxiv.org/abs/2504.05684).
-
-## To-Dos
-- [x] Release model weights on Google Drive.
-- [x] Release inference code
-- [x] Release training code & dataset preparation
-
-## ⚙️ Environmental Setups
-1. Clone TARO.
-```bash
-git clone https://github.com/triton99/TARO
-cd TARO
-```
-
-2. Create the environment.
-```bash
-conda create -n taro python==3.10
-conda activate taro
-pip install torch==2.1.0 torchvision==0.16.0 torchaudio==2.1.0 --index-url https://download.pytorch.org/whl/cu121
-
-# Training
-pip install --force pip==24.0
-git clone https://github.com/pytorch/fairseq
-cd fairseq
-pip install --editable ./ --no-build-isolation
-cd ..
-
-git clone https://github.com/cwx-worst-one/EAT.git
-
-# Inference
-pip3 install -r requirements.txt
-```
-
-## 📁 Data Preparations
-Please download the [VGGSound dataset](https://www.robots.ox.ac.uk/~vgg/data/vggsound/), extract the videos, and organize them into two folders: one with .mp4 files and one with corresponding .wav files (matching base filenames). 
-
-Update the path variables at the top of the preprocessing scripts to point to your folders, then run:
-```bash
-./preprocess_video.sh
-
-./preprocess_audio.sh
-```
-
-After processing, the data will have the following structure:
-```bash
-VGGSound/train
-    ├── videos
-    │   ├── abc.mp4
-    │   └── ...
-    ├── audios
-    │   ├── abc.wav
-    │   └── ...
-    ├── cavp_feats
-    │   ├── abc.npz
-    │   └── ...
-    ├── onset_feats
-    │   ├── abc.npz
-    │   └── ...
-    ├── melspec
-    │   ├── abc.npy
-    │   └── ...
-    └── fbank
-    │   ├── abc.npy
-    │   └── ...
-```
-
-
-## 🚀 Getting Started
-
-### Download Checkpoints
-
-The pretrained TARO checkpoint can be downloaded on [Google Drive](https://drive.google.com/drive/folders/1YqLsEtVYeSchhAh-wKS-BWuB6MK6_mJB?usp=sharing).
-
-The CAVP checkpoint can be downloaded from [Diff-Foley](https://github.com/luosiallen/Diff-Foley).
-
-The onset checkpoint can be downloaded from [SyncFusion](https://github.com/mcomunita/syncfusion).
-
-### Training
-```bash
-./train.sh
-```
-
-### Inference
-To run the inference code, you can use the following command:
-```bash
-python infer.py \
-    --video_path ./test.mp4 \
-    --save_folder_path ./output \
-    --cavp_config_path ./cavp/model/cavp.yaml \
-    --cavp_ckpt_path ./cavp_epoch66.ckpt \
-    --onset_ckpt_path ./onset_model.ckpt \
-    --model_ckpt_path ./taro_ckpt.pt
-```
-
-## 📖 Citing TARO
-
-If you find our repository useful, please consider giving it a star ⭐ and citing our paper in your work:
-
-```bibtex
-@inproceedings{ton2025taro,
-  title     = {TARO: Timestep-Adaptive Representation Alignment with Onset-Aware Conditioning for Synchronized Video-to-Audio Synthesis},
-  author    = {Ton, Tri and Hong, Ji Woo and Yoo, Chang D},
-  year      = {2025},
-  booktitle = {International Conference on Computer Vision (ICCV)},
-}
-```
-
-## 🤗 Acknowledgements
-
-Our code is based on [REPA](https://github.com/sihyun-yu/REPA), [Diff-Foley](https://github.com/luosiallen/Diff-Foley), and [SyncFusion](https://github.com/mcomunita/syncfusion). We thank the authors for their excellent work!
+---
+title: TARO
+emoji: 🎬
+colorFrom: blue
+colorTo: purple
+sdk: gradio
+sdk_version: 5.20.1
+app_file: app.py
+pinned: false
+license: mit
+short_description: Video-to-Audio Synthesis with TARO (ICCV 2025)
+---
+
+# TARO: Video-to-Audio Synthesis
+
+Upload a video and generate synchronized audio using TARO (ICCV 2025).