Closed ksnzh closed 6 years ago
If I use the task model and the L1 and smooth loss introduced in the article for supervised depth estimation, will the model achieve the reported score on NYU depth dataset as the f_T-only Benchmark Models shows?
Yes, for task model, you can change the img_source
to NYU_TRAIN_IMAGE, lab_source
to NYU_TRAIN_DEPTH, img_target
to NYU_TEST_IMAGE, 'lab_target' to NYU_TEST_IMAGE.
In our task, the
img_source
andlab_source
indicate the synthetic image and depth respectively, andimg_target
and 'lab_target' indicate the real world image and depth respectively. If you want to do other tasks, you can change the label, like the semantic label.