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--- |
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pretty_name: EventRain-27K |
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license: mit |
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tags: |
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- dataset |
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- event-camera |
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- neuromorphic-vision |
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- rain |
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--- |
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<p align="center"> |
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<h1 align="center" style="display: flex; align-items: center; justify-content: center;"> |
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<img src="./assets/logo.png" alt="Logo" width="55" height="55" style="margin-right: 10px;"> |
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<font size="7">EventRain-27K</font> |
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</h1> |
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<div align="center"> |
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<!-- Paper badge --> |
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<a href="https://arxiv.org/abs/2505.05307"> |
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<img src="https://img.shields.io/badge/paper-arXiv-B31B1B.svg" style="height:28px;"> |
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</a> |
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<!-- Dataset badge --> |
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<a href="https://huggingface.co/datasets/Rshnn/EventRain-27K/blob/main/README.md"> |
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<img src="https://img.shields.io/badge/dataset-EventRain--27K-blue?logo=huggingface" style="height:28px;"> |
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</a> |
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<!-- License badge --> |
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<a href="https://opensource.org/licenses/MIT"> |
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<img src="https://img.shields.io/badge/license-MIT-green.svg" style="height:28px;"> |
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</a> |
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</div> |
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<p align="center"> |
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<!-- 横幅：可用相对路径(推荐)或外链 --> |
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<img src="assets/EventRain-27K_samples.png" alt="EventRain-27K Overview" width="70%"> |
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</p> |
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--- |
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## Source Paper |
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<div align="center"> |
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<font size="5"><b>PRE-Mamba: A 4D State Space Model for Ultra-High-Frequent Event Camera Deraining</b></font> |
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<p><i>ICCV, 2025</i></p> |
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<a href="https://arxiv.org/abs/2505.05307"> |
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<img src="https://img.shields.io/badge/arXiv-2505.05307-B31B1B.svg"> |
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</a> |
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</div> |
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--- |
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## Description |
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- **Synthetic datasets (KITTI & SPAC).** Event streams are partitioned into contiguous windows of Δt = 0.1 s (10^8 ns per segment) and stored in `.npz` files. The `merge_data` directory contains background–rain composites, while `raw_data` contains background-only events. Each `.npz` stores the arrays `['x', 'y', 't', 'p']`. |
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- **Prophesee EVK4 recordings (artificial rain & real-world).** Raw `.raw` event streams are converted to `.npz` and segmented into Δt = 0.1 s (10^5 μs per segment), with the same keys `['x', 'y', 't', 'p']`. For the artificial-rain subset, labels are generated using a K-Nearest Neighbors (KNN) procedure: background events in rainy sequences are identified via spatiotemporal alignment with corresponding rain-free data. Label files are provided in `.npy` format. |
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## Dataset Structure |
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```text |
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EventRain-27K/ |
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├── synthetic/ |
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| ├── synthetic_KITTI/synthetic/ # Resolution:(460, 352) |
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| | ├── merge_data/ # File type: .npz (background + rain) |
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| | └── raw_data/ # File type: .npz (background) |
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| └── synthetic_SPAC/ # Resolution:(640, 480) |
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| ├── SPAC-dataset-merge/ # File type: .npz (background + rain) |
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| └── SPAC-dataset-event/gt/ # File type: .npz (background) |
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└── real/ |
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├── EVK4_artifical/ # Resolution:(1280, 720) |
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| ├── scene{i:1-4}/ |
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| | ├── labels/ # File type: .npy (labels: 0/1 >> rain/background) |
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| | └── merge_data/ # File type: .npz |
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└── EVK4_realworld/ |
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└── scene{i:5}/ |
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└── merge_data/ # File type: .npz |
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``` |
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## Dataset Usage |
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The data can be placed under this directory. Taking SYTHETIC_DATA as an example, the data is divided and processed according to time windows into the following directory structure: |
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```text |
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data/ |
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└── synthetic/ |
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│ └── SYNTHETIC_DATA_DIR/ |
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│ └── synthetic/ |
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│ ├── merge_data/ |
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│ │ ├── 1mm/ |
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│ │ │ ├── 0000000000.npz |
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│ │ │ ├── ... |
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│ │ │ └── 0000000388.npz |
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│ │ ├── 5mm/ |
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│ │ │ ├── 0000000000.npz |
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│ │ │ ├── ... |
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│ │ │ └── 0000000388.npz |
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│ │ ├── 10mm/ |
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│ │ │ └── ... |
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│ │ ├── ... |
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│ │ └── 200mm/ |
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│ │ ├── 0000000000.npz |
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│ │ ├── ... |
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│ │ └── 0000000388.npz |
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│ └── raw_data/ |
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│ ├── 0000000000.npz |
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│ ├── ... |
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│ └── 0000000388.npz |
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└── real/ |
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└── EVK4_DATA_DIR/ # EVK4_artificial(scene 1-4) and EVK4_realworld(scene 5) |
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└── scene{i}/ # Take scene1 as an example |
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├── merge_data/ |
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│ ├── rain_0/ |
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│ │ ├── 0000000000.npz |
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│ │ ├── ... |
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│ │ └── 0000000165.npz |
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│ ├── rain_1/ |
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│ │ ├── 0000000000.npz |
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│ │ ├── ... |
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│ │ └── 0000000182.npz |
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│ ├── rain_2/ |
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│ │ └── ... |
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│ ├── ... |
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│ └── rain_3/ |
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│ ├── 0000000000.npz |
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│ ├── ... |
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│ └── 0000000166.npz |
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└── labels/ |
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│── labels_rain_0/ |
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│ ├── labels_0000000000.npy |
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│ ├── ... |
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│ └── labels_0000000165.npy |
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├── labels_rain_1/ |
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│ ├── labels_0000000000.npy |
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│ ├── ... |
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│ └── labels_0000000182.npy |
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├── labels_rain_2/ |
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│ └── ... |
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├── ... |
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└── labels_rain_3/ |
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├── labels_0000000000.npy |
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├── ... |
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└── labels_0000000166.npy |
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``` |
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