# Official PyTorch Implementation for InfoSwap: Information Bottleneck Disentanglement for Identity Swapping

### Related tags

Deep Learning InfoSwap-master

## InfoSwap: Information Bottleneck Disentanglement for Identity Swapping

### Code usage

Please check out the user manual page.

### Paper

Gege Gao, Huaibo Huang, Chaoyou Fu, Zhaoyang Li, Ran He, "Information Bottleneck Disentanglement for Identity Swapping", CVPR 2021

### Citation

If you find this code useful for your research, please cite our paper:

``````@InProceedings{Gao_2021_CVPR,
author    = {Gao, Gege and Huang, Huaibo and Fu, Chaoyou and Li, Zhaoyang and He, Ran},
title     = {Information Bottleneck Disentanglement for Identity Swapping},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month     = {June},
year      = {2021},
pages     = {3404-3413}
}
``````
• #### 太棒的思想了，看源码有个问题

iib.py里面 191行，标准差为什么取的是均值呢？不太懂 m_s = torch.mean(Rs, dim=0) # [C, H, W] std_s = torch.mean(Rs, dim=0) Rs_params.append([m_s, std_s]) eps_s = torch.randn(size=Rt.shape).to(Rt.device) * std_s + m_s feat_t = Rt * (1. - lambda_t) + lambda_t * eps_s Xt_feats.append(feat_t) # only related with lambda

``````        m_t = torch.mean(Rt, dim=0)  # [C, H, W]
std_t = torch.mean(Rt, dim=0)
Rt_params.append([m_t, std_t])
eps_t = torch.randn(size=Rs.shape).to(Rs.device) * std_t + m_t
feat_s = Rs * (1. - lambda_s) + lambda_s * eps_t
Xs_feats.append(feat_s)  # only related with lambda
``````
opened by dayu1979 2
• #### An inconsistency of the input of IBLayer

In inference_demo.py, R = encoder.features[i]; while in the forward function of IIB, R = readout_feats[i]. Which should I use for training? And when I use R = readout_feats[i], Info is really large (5668875) at the beginning of training.

opened by lyx0208 1
• #### FileNotFoundError: [Errno 2] No such file or directory: './checkpoints_512/w_kernel_smooth\\ckpt_ks_G.pth'

Hello, I have the following problem now. Could you please provide me with this checkpoint? Thank you

FileNotFoundError:No such file or directory: './checkpoints_512/w_kernel_smooth\ckpt_ks_G.pth'

opened by an-zi-li 1
• #### About the encoders, decoders and AII generators

According to the pseudo code "Algorithm 1" in the supp.pdf file, there are 2 pretrained encoders, 3 decoders and 2 AII generators.

For the encoders and decoders, if I only use 1 module and use it several times during the training, I have this error: RuntimeError: one of the variables needed for gradient computation has been modified by an inplace operation It's OK to copy a encoder as it's pretrained and I do not need to optimize it during training. But for the decoder, I think its not proper to copy it 3 times, as according to my understanding of the algorithm, the three parts should use decoder with the same parameter.

For the AII generator, I think I just need to have two generators with the same structure, just as the cycle gan has two generators. And I can use the Lcyc in line 41 to optimize these two generators together. Is this understanding right?

opened by lyx0208 1
• #### source-to-target pairs

Hi, thanks for your great work!

For the quantitative results in your work，I have questions about the correspondence of pair frames from source and target videos respectively.

(1) Did you randomly select 10 frames from each video or get the same pairs as FaceShifter?

(2) Could you provide the source-to-target pairs numbers for further fair comparison?

Thanks!

opened by ZekuiQin 1
###### Grace Hešeri
I'm currently working in the National Laboratory of Pattern Recognition (NLPR). My scientific interests are in the field of computer vision and machine learning
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