Comments (1)
Hello @NanAlbert,
Regarding fine-tuning, what we mean is that the Imagenet-trained Resnet backbone is independently finetuned on the seen classes for each dataset. Once the finetuning is completed for the backbone, features for the images are extracted and used as input to the VAEGAN. This was the procedure used in the baseline f-VAEGAN-d2 paper (CVPR 19). The entire Resnet was finetuned with a low lr of 1e-5 or 1e-6.
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Related Issues (20)
- Could you share the codes to fineturn resnet, extract visual features and generate .mat files? HOT 1
- Question on training custom dataset HOT 3
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- Transductive Setting HOT 6
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- classify HOT 5
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- There is a gap in performance than in the paper HOT 7
- Question about argparse HOT 2
- Questions about training HOT 10
- What is the training unseen feature under transductive setting?
- Question about training on action recognition HOT 1
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