Learning to Watermark in Latent Space
Project description
DistSeal
Official implementation of DistSeal, a unified framework for latent watermarking that works across both diffusion and autoregressive models. In the 🚀 Usage sections, we show examples of in-model watermarking and post-hoc latent watermarking for the diffusion model DC-AE and the autoregressive model RAR. We provide the model checkpoints from the paper, as well as the training code to reproduce them.
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file distseal-0.0.2.tar.gz.
File metadata
- Download URL: distseal-0.0.2.tar.gz
- Upload date:
- Size: 5.8 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: python-requests/2.32.5
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
6ef2436b9488281e192cb13ebc0b7b618b0a9e5a64e71fe98149c87379edbcb6
|
|
| MD5 |
c3c45fdce59d6b176db3285fd60551e4
|
|
| BLAKE2b-256 |
52e6a81e420863e0b93621e7cca6e99e7967ec227a207396949fc7e2a9203108
|
File details
Details for the file distseal-0.0.2-py3-none-any.whl.
File metadata
- Download URL: distseal-0.0.2-py3-none-any.whl
- Upload date:
- Size: 5.3 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: python-requests/2.32.5
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
39ac587aebed91553e14495f1e260712ab33174038d62ba1275f63308660149a
|
|
| MD5 |
61e7ecd5835b8196f536020a5a882fab
|
|
| BLAKE2b-256 |
b4218cb19ce6989f3f17f8a45c414960e3e15b05402c9e7f9a52210c9b6637eb
|
