README.md

---
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`.