| --- |
| 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. |
|
|
