Hierarchical Memory Matching Network for Video Object Segmentation (ICCV 2021)

Hi,

THX for releasing the inference code of DAVIS.

May I ask what frame rate did you use in the evaluation of HMMN and KMN on YouTube-VOS? Validation or Validation All Frames? 6FPS or 30FPS?

Best.

thanks for your sharing . wonderful job, but why i didn't see the dropout in top-k guided memory matching and the conv3*3 before it in your code. and the KV_Q_r3 = KeyValue(512, keydim=128, valdim=-1, only_key=True) means there is no need for values. What do I understand it ?

Excellent work! I have some question about the dropout in the top-k guided memory matching module and the value of query(r2,r3). In your code, you doesn't use the value of query of r2 and r3 stage, but in the paper you use the value to generate Z3. The operation in the code is different from the description in the paper.

I noticed that this code only included evaluation part and lack the training part. It would be really helpful if you could proide the training code. Another question is that the model in this code has some differences compared to the paper. In the top-k guided memory matching module, the model in this code don't have the VQ3 add to the result which come out from dropout. Instead, it directly uses results after the second ''matmul'' as the output of the top-k module (in Figure.6 in the paper this is Z4). Could you please explain the reason? Moreover, I wonder if I need to add a dropout layer, a conv3 layer and a ''VQ3 add.'' layer when training the model. Of course if you can provide me with your training code, it would be most helpful! Thank you for your time!