Comments (3)
Hello, n-way and k-shot specify the parameter in meta-training methods in the meta-training stage. For Baseline and Baseline++, it always trains a classifier for all class with all data in training stage.
from closerlookfewshot.
yes,I saw the content in code。However, there were five shot and one shot of baseline and baesline++ comparison in experiment result. How that happened
from closerlookfewshot.
yes,I saw the content in code。However, there were five shot and one shot of baseline and baesline++ comparison in experiment result. How that happened
For novel class which contains few samples per class, we do train the classifier of both baseline and baseline++ in the "few-shot method" (i.e., using the few samples from the novel class).
As both meta-learning method and our baseline methods use the same amount of training samples (abundant samples from the base class and few samples from the novel class), we thus present the comparison in our paper.
Please have a look at our paper.
from closerlookfewshot.
Related Issues (20)
- Training accuracies are low and their gaps are big when Conv4 backbone is used.
- Question on feature_loader.py:32,33
- The stop_epoch number of maml
- Larger batch size for CUBS.
- Query Regarding Figure 5.
- TypeError: super() argument 1 must be type, not classobj
- assert params.num_classes >= 1597, 'class number need to be larger than max label id in base class' HOT 5
- h
- Training using 'protonet', 'matchingnet', 'relationnet', 'relationnet_softmax', 'maml', 'maml_approx' methods with an unbalanced dataset.
- Baseline++ cross_char accuracy lower than Baseline
- About the lacking of query sample in data_loader and the lacking of target in calculating loss
- h
- CUB dataset's link no longer valid
- Baseline ++ validation wrongly reported in paper?
- What does fid mean in write_miniImagenet_filelist.py ?
- How to fine-tune the Matching Network HOT 1
- errro _pickle.PicklingError HOT 1
- RuntimeError: "nll_loss_forward_reduce_cuda_kernel_2d_index" not implemented for 'Int'
- how to make the experiments repeatable?
- How to get the pre-trained model?
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from closerlookfewshot.