Bohao-Lee
commented
3 years ago For the first question, we use CME to imporve MPSR's classfication, so we use it in refinement branch, not another branch. For the second question, we view margin as inter-class distance as margin. Hope this paper can help u. (https://arxiv.org/pdf/2005.13826.pdf)
Sorry, I still don't understand. CME is meta-learning based method, however, MPSR is fine-tuning method without support branch, so how to implement Feature Disturbance while there is no support mask?
Sorry, we use Feature Disturbance to disturb feature. Because mask reflects object position, we use it. You can disturb corresponding object in image or corresponding feature. Because of limited time, we don't more experiment in it. We'll try to do some research in it.
Originally posted by @Bohao-Lee in #1 (comment)
Hello! I noticed that the MPSR-based method has better performance. Will you release the code of that? 😁 And I am also interested in how the Feature Disturbance work in MPSR. Did you mean the structure of MPSR hadn't been changed, and the network was directly fine-tuned with the disturbed features? Looking forward to your reply
Thank you for your attention to our project. In fact, we are trying to improve CME and making a second version. We'll show it later and also CME for other baseline
Sorry, we use Feature Disturbance to disturb feature. Because mask reflects object position, we use it. You can disturb corresponding object in image or corresponding feature. Because of limited time, we don't more experiment in it. We'll try to do some research in it.
Originally posted by @Bohao-Lee in https://github.com/Bohao-Lee/CME/issues/1#issuecomment-815551915
Hello! I noticed that the MPSR-based method has better performance. Will you release the code of that? 😁 And I am also interested in how the Feature Disturbance work in MPSR. Did you mean the structure of MPSR hadn't been changed, and the network was directly fine-tuned with the disturbed features? Looking forward to your reply