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Can you provide more details of different methods and their tunable parameters in Table 4 for semantic segmentation?
Except for header parameters:
1)the tunable parameter number of BIAS is 13.46-13.18=0.28M
2)the tunable parameter number of VPT is 13.43-13.18=0.25M
3) why is the tunable parameter number of VPT+BIAS 15.79-13.18=2.61M, rather than 0.28+0.25=0.53M?
It seems to me that BIAS was reimplemented based on the paper [5] (fine-tunes only the bias terms).
However, was VPT+BIAS reimplemented based on the paper [8] (fine-tunes the bias terms and introduces some lightweight residual layers)?
The text was updated successfully, but these errors were encountered:
Hi @liulingbo918 Thanks for your question. The reason for this difference is that VPT-deep and VPT+Bias use different number of prompts as hyperparameter. VPT-deep uses p=10, whereas VPT+BIAS uses p=100. Since VPT+BIAS use 10 times of prompts than VPT_deep, the tunable parameters of VPT+BIAS = 0.28 + 0.25 x10
Can you provide more details of different methods and their tunable parameters in Table 4 for semantic segmentation?
Except for header parameters:
1)the tunable parameter number of BIAS is 13.46-13.18=0.28M
2)the tunable parameter number of VPT is 13.43-13.18=0.25M
3) why is the tunable parameter number of VPT+BIAS 15.79-13.18=2.61M, rather than 0.28+0.25=0.53M?
It seems to me that BIAS was reimplemented based on the paper [5] (fine-tunes only the bias terms).
However, was VPT+BIAS reimplemented based on the paper [8] (fine-tunes the bias terms and introduces some lightweight residual layers)?
The text was updated successfully, but these errors were encountered: