---
task_categories:
- image-to-image
---

<div align="center">

<h1 style="border-bottom: none;">🎥 SportsSloMo-CVS Dataset</h1>

[![arXiv](https://img.shields.io/badge/arXiv-Paper-b31b1b.svg?logo=arxiv)](https://arxiv.org/abs/2604.10554)
[![Project Page](https://img.shields.io/badge/🏠-Project%20Page-blue.svg)](https://tmcdeblur.github.io/)
[![GitHub](https://img.shields.io/badge/GitHub-Code-black.svg?logo=github)](https://github.com/Tianmouc/tmcDeblur)
[![GitHub](https://img.shields.io/badge/GitHub%20Org-TianMouCV-black.svg?logo=github)](https://github.com/Tianmouc)

</div>

This repository contains the dataset presented in the paper [Spatio-Temporal Difference Guided Motion Deblurring with the Complementary Vision Sensor](https://huggingface.co/papers/2604.10554).

The Complementary Vision Sensor (CVS), known as Tianmouc, captures synchronized RGB frames together with high-frame-rate, multi-bit spatial difference (SD, encoding structural edges) and temporal difference (TD, encoding motion cues) data within a single RGB exposure. This dataset facilitates research in RGB deblurring under extreme dynamic scenes by leveraging these complementary modalities.


# 📦 Dataset Overview

This is a large-scale, real-captured and pixel-level aligned dataset with diverse scenes, supporting multi-exposure and multi-form motion deblurring with CVS.

It contains:

- **98,569** training pairs  
- **1,928** validation pairs  
- **1,820** test pairs  

Each clip folder represents one continuous motion scene.




# 📂 Directory Structure


| Root | RGB Exposure Time (us) | Blur Length | Log |Description |
|--------|------------|------------|------------|------------|
| `Tianmouc_dataset_SportsSloMo_1160_1000_14520_1240/` | 14,520 |11 | `log_1160_1000_14520_1240_filtered_fixed.csv` |heavy blur |
| `Tianmouc_dataset_SportsSloMo_1560_870_11880_1240/`  | 11,880 |9  | `log_1560_870_11880_1240_filtered_fixed.csv`  |medium-heavy blur |
| `Tianmouc_dataset_SportsSloMo_1480_1150_9240_1240/`  | 9,240  |7  | `log_1480_1150_9240_1240_filtered_fixed.csv`  |medium blur |
| `Tianmouc_dataset_SportsSloMo_2830_880_6600_1240/`   | 6,600  |5  | `log_2830_880_6600_1240_filtered_fixed.csv`   |light blur |
| `Tianmouc_dataset_SportsSloMo_cop_parts/`            | - | - | - | GT |
| `group_gt_parts/`                                    | - | - | - | the original images used for making the dataset |

<!-- Each path corresponds to a different exposure condition in COP. -->


# 🔀 Train / Val / Test Split

Controlled by:
- `val_clip_info.txt`
- `test_clip_info.txt`

Rules:
- Train: excludes val/test clips
- Val/Test: only includes specified clips


# 👀 Data Preview

### 1. Install tianmoucv


```bash
pip install tianmoucv
```

### 2. Quick Data Preview

We provide a Jupyter Notebook to help you quickly visualize the data. (**[link](https://github.com/Tianmouc/tmcDeblur/blob/master/data/SportsSloMo-CVS/SportsSloMo-CVS_preview.ipynb)**)