| Input: Unpaired real-world data: Su; |
| Paired synthetic data: Sp; |
| Batch sizes for Su and Sp : x and y; |
| Indicator function: Sm. |
|
| 1. Load the pretrained models P and u; |
| 2. while not convergent do |
| 3. Sample unlabeled data {xi} from SU; |
| 4. Sample labeled data {(xi, yi)} from SP; |
| 5. // Update the primal mode |
| 6. Update P by minimizing the objective: |
| 7.
\sum\limits_{i = 1}^{m + n} {{I_{{s_p}}}\left( {{x_i}} \right){\iota _p}\left( {P\left( {{x_i}} \right),{y_i}} \right) + \lambda {\iota _D}\left( {D\left( {P\left( {{x_i}} \right)} \right),{x_i}} \right)}
|
| 8. // Update the dual model |
| 9. Update D by minimizing the objective: |
| 10.
\sum\limits_{i = 1}^{m + n} {\lambda {\iota _p}\left( {D\left( {P\left( {{x_i}} \right)} \right),{x_i}} \right)}
|
| 11. END |
