Comments (2)
The fine-tuning part is not the focus of this paper, but we promise the results are reproducible and will make it public after the conference.
If it's urgent for you, you can refer to FewX code library, where fine-tuning can be achieved, then you may modify our code accordingly.
But remember to double check one-shot setting, there is a bug.
from airdet.
The fine-tuning part is not the focus of this paper, but we promise the results are reproducible and will make it public after the conference. If it's urgent for you, you can refer to FewX code library, where fine-tuning can be achieved, then you may modify our code accordingly. But remember to double check one-shot setting, there is a bug.
Hi! May I ask the fine-tuning time of your method?
from airdet.
Related Issues (14)
- IndexError: list index out of range HOT 2
- "ignore" in COCO json file is not supported HOT 1
- The performance of other methods in Table 1 HOT 1
- the question of Numclass seting HOT 1
- Inference HOT 1
- Test result of COCO dataset HOT 1
- In COCO, I Get a very low AP score, how can I fix it? HOT 7
- How to train on self-define dataset HOT 2
- Correct supports cannot be generated in the VOC dataset HOT 1
- Efficiency HOT 1
- The weight of R101 provided HOT 1
- The trained model is not available HOT 3
- cuda out of memory HOT 1
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