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View Code? Open in Web Editor NEW[IJCAI 2021 & AIJ 2023] Cross-Domain Few-Shot Classification via Adversarial Task Augmentation
[IJCAI 2021 & AIJ 2023] Cross-Domain Few-Shot Classification via Adversarial Task Augmentation
hello, I tried to get plantae dataset by link you provided in process.py but the website it points responded with "404 not found".
Could you please provide a new link? Thanks!
Hi, thanks for you sharing codes. Here I have a question about which model exactly you used when test in cross-domain few-shot dataset in table 1. For example, you use the one tested best in mini-test or you have another evaluation to choose the model which can generalize best in all this datasets? Looking forward to your response, thanks.
Nice work! However, I cannot reimplement the result in table 1 using the GNN method. I notice that your finetune.py document also covers the augmentation method. I finetuned the GNN checkpoint which was trained by step 1 and get very low accuracy using the finetune.py from https://github.com/IBM/cdfsl-benchmark. So can you provide me some detailes on how to get the GNN results in table 1. Also, I noticed that your code can not cover more shots(5way-20s or 5w-50s), since this may cost more CUDA memerory, have you solved this issue?
Hello, your work has inspired me a lot! I hope to further study and re-implement your result, but I found that using different pre-training models (specifically the "399.tar" in your code) had a great impact on the result. However, I used a variety of pre-training weights but did not get the result as in your paper. Could you please public pretrained model weights you used for different methods? Thanks a lot!
Hello, the dataset download links of cars, miniImagenet and planate in filelists->process.py are wrong, can you provide a right link? Many thanks.
Dear authors:
I find no supplementary material for the paper "Cross-Domain Few-Shot Classification via Adversarial Task Augmentation".
The conclusions in Lemma1 and Lemma 2 seem a little hard to deduce by myself. And the given references are full of too much distractors that I can't grasp the key content.
Could you please give me more explanation or some proof material about Lemma1 and Lemma 2?
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