ControlNet
/

marlin_vit_large_ytf

@@ -1,199 +1,60 @@
 ---
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 ---
 library_name: transformers
+tags:
+- video
+- feature
+- face
+license: cc
+base_model:
+- ControlNet/MARLIN
+pipeline_tag: feature-extraction
 ---
+# MARLIN: Masked Autoencoder for facial video Representation LearnINg
+This repo is the official PyTorch implementation for the paper
+[MARLIN: Masked Autoencoder for facial video Representation LearnINg](https://openaccess.thecvf.com/content/CVPR2023/html/Cai_MARLIN_Masked_Autoencoder_for_Facial_Video_Representation_LearnINg_CVPR_2023_paper) (CVPR 2023).
+## Use `transformers` (HuggingFace) for Feature Extraction
+Requirements:
+- Python
+- PyTorch
+- transformers
+- einops
+Currently the huggingface model is only for direct feature extraction without any video pre-processing (e.g. face detection, cropping, strided window, etc).
+```python
+import torch
+from transformers import AutoModel
+model = AutoModel.from_pretrained(
+    "ControlNet/marlin_vit_base_ytf",  # or other variants
+    trust_remote_code=True
+)
+tensor = torch.rand([1, 3, 16, 224, 224])  # (B, C, T, H, W)
+output = model(tensor)  # torch.Size([1, 1568, 384])
+```
+## License
+This project is under the CC BY-NC 4.0 license. See [LICENSE](LICENSE) for details.
+## References
+If you find this work useful for your research, please consider citing it.
+```bibtex
+@inproceedings{cai2022marlin,
+  title = {MARLIN: Masked Autoencoder for facial video Representation LearnINg},
+  author = {Cai, Zhixi and Ghosh, Shreya and Stefanov, Kalin and Dhall, Abhinav and Cai, Jianfei and Rezatofighi, Hamid and Haffari, Reza and Hayat, Munawar},
+  booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
+  year = {2023},
+  month = {June},
+  pages = {1493-1504},
+  doi = {10.1109/CVPR52729.2023.00150},
+  publisher = {IEEE},
+}
+```