---
license: mit
library_name: pytorch
tags:
  - machine-unlearning
  - person-re-identification
  - vehicle-re-identification
  - privacy
  - membership-inference
  - image-retrieval
pipeline_tag: image-feature-extraction
---

# MoME: Forget the Data, Keep the Capability

Weights for **MoME**, which splits one re-identification backbone into core parameters that
preserve retrieval and zero-initialized parasitic parameters that carry the full-data knowledge,
trained under gradient isolation so the core never receives a forget-set gradient. One checkpoint
is read two ways: with the branch off it satisfies a request to delete a person's training data,
with the branch on it restores what that data taught.

Paper: <https://arxiv.org/abs/2610.36858> · Code: <https://github.com/Jingong-Chen/MoME>

## Files

| File | What it is | mAP | R-1 |
|:---|:---|:---:|:---:|
| `market/mome_core.pth` | MoME on Market-1501, read with `--mode core` | 74.3 | 88.2 |
| `market/mome_full.pth` | the consolidated payload for Market-1501 | 88.7 | 95.2 |
| `market/retrain_s42.pth` | the retrained reference the tables compare against | 70.5 | 86.9 |
| `market/original.pth` | trained on everything, no deletion | 88.0 | 94.8 |
| `veri/mome_core.pth` | MoME on VeRi-776, read with `--mode core` | 42.8 | 69.6 |
| `veri/original.pth` | trained on everything, no deletion | 82.3 | 97.1 |

All are ViT-B/16 at 256 × 128, initialized from the ImageNet ViT the TransReID recipe uses. The
deletion request is identity-level: split seed 42, half the identities deleted, four images kept
per retained identity. Each file reads its own number rather than the five-split mean the paper's
tables report.

The VeRi-776 payload is not here as a file. It is thirty epochs from `veri/mome_core.pth` and
`veri/original.pth` with `scripts/full_fit.py`, which is how the one in the paper was made; the
command is in the repository README.

## Use

```python
from utils.parasitic_utils import set_parasitic_mode

set_parasitic_mode(model, False)   # Core: the deletion request is honored
set_parasitic_mode(model, True)    # Full: the full-data model is back
```

```bash
python eval_partition.py --config_file configs/Market/vit_transreid_stride_mome_v3.yml \
  --weight market/mome_core.pth --mode core
```

## Citation

```bibtex
@article{chen2026mome,
  title   = {Forget the Data, Keep the Capability: Switchable Unlearning for Retrieval},
  author  = {Chen, Jingong and Gao, Kyle and Li, Guangyuan and Pack, Chulwoo and
             Liu, Sijia and Won, Kwanghee},
  journal = {arXiv preprint arXiv:2610.36858},
  year    = {2026}
}
```

## Licence

MIT, as the code is. The datasets these were trained on are not redistributed and keep the terms
of their own releases.