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license: cc-by-4.0
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# CoherentGS-DL3DV-Blur Dataset
## Motivation 💡
To rigorously assess the generalization capability of **CoherentGS** in complex, unconstrained outdoor environments, we establish a new benchmark named **DL3DV-Blur**. This benchmark is derived from five diverse scenes within the DL3DV-10K dataset.
> **Citation Reference:** Ling et al. (2024). DL3DV-10K: A Large-scale Dataset for Deep Learning-based 3D Vision.
> [https://arxiv.org/abs/2312.16256](https://arxiv.org/abs/2312.16256)
## Dataset Source 🔗
This dataset is constructed from select scenes of the official DL3DV-10K repository.
- **DL3DV-10K GitHub:** https://github.com/DL3DV-10K/Dataset
## Data Format 📂
The dataset structure adheres to standard 3D vision dataset formats, where each scene (e.g., `0001`) contains sub-folders for different view configurations (e.g., `3views`, `6views`, `9views`).
### Structure Overview
The hierarchical structure of the data is as follows:
```text
dl3dv/
├── 0641-0720/
│ ├── 0001/ # Scene ID 0001
│ │ ├── .work/
│ │ ├── 3views/ # 3-View Sub-set
│ │ │ ├── images/ # Raw input image files
│ │ │ ├── ref_image/ # Reference Image
│ │ │ ├── sparse/ # Sparse reconstruction results (e.g., COLMAP output)
│ │ │ ├── cameras.json # Camera parameter file
│ │ │ ├── ext_metadata.json # Additional metadata
│ │ │ ├── hold=7 # Test set configuration
│ │ │ ├── intrinsics.json # Camera intrinsics
│ │ │ ├── poses_bounds.npy # Camera poses and scene bounds
│ │ │ ├── train_test_split_3.json # Train/Test split definition
│ │ │ └── transforms.json # Coordinate transformation info
│ │ ├── 6views/ # 6-View Sub-set
│ │ └── 9views/ # 9-View Sub-set
│ ├── 0002/
│ ├── 0003/
│ ├── 0004/
│ └── 0005/
└── ...
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