Datasets:
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license: other
task_categories:
- image-segmentation
tags:
- camouflaged-object-detection
- cod
- segmentation
- cod-tdq
---
# 🦎 COD Dataset Bundle For COD-TDQ
This repository hosts the camouflaged object detection dataset bundle used by:
**When W4A4 Breaks Camouflaged Object Detection: Token-Group Dual-Constraint Activation Quantization**
- Paper: https://arxiv.org/abs/2604.16855
- Code: https://github.com/MCG-NKU/nku-model-compre/tree/main/cod-tdq
This dataset repository contains the COD resource bundle used by the release:
TrainValDataset plus CHAMELEON, CAMO, COD10K and NC4K test sets.
## Layout
```text
Dataset/
├── TrainValDataset/{Imgs,GT,Edge}
└── TestDataset/
├── CHAMELEON/{Imgs,GT,Edge}
├── CAMO/{Imgs,GT,Edge}
├── COD10K/{Imgs,GT,Edge}
└── NC4K/{Imgs,GT,Instance}
```
## Counts
| Split / Dataset | Images |
| --- | ---: |
| TrainValDataset | 4040 |
| CHAMELEON | 76 |
| CAMO | 250 |
| COD10K | 2026 |
| NC4K | 4121 |
## Usage
Use this dataset with the official code:
```bash
git clone https://github.com/MCG-NKU/nku-model-compre.git
cd nku-model-compre/cod-tdq
```
Expected local layout:
```text
assets/datasets/cod/
├── TrainValDataset/{Imgs,GT,Edge}
└── TestDataset/{CHAMELEON,CAMO,COD10K,NC4K}
```
If you download this repository directly, move or symlink `Dataset/TrainValDataset` and
`Dataset/TestDataset` into `assets/datasets/cod/`.
## Citation
```bibtex
@inproceedings{codtdq2026,
title={When W4A4 Breaks Camouflaged Object Detection: Token-Group Dual-Constraint Activation Quantization},
author={Coming Soon},
booktitle={ECCV},
year={2026}
}
```
Please also cite the original datasets according to their respective licenses.
## Integrity
Checksums are provided in `SHA256SUMS`.
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