260k interations, mPCP on LSP is close to 0.42 with Imagenet initialization

[jjzhang10]

I train the LSP dataset with imagenet initialization. It has been 260k iterations, the train/pose_error is around[0.02 0.03]. The mPCP score (0.42) is still far from the result listed in the table. It does increase, but pretty slowly.

Does it mean it cannot converge for this time? I need restart the training? Thanks.

[asanakoy]

Looks like you initialized it randomly. On my experience Radom initialization achieves PCP score ~0.42

[jjzhang10]

@asanakoy I forget to add the parameter "fix_conv_lr 10000". Training the conv and fc weights together at the very beginning may hurt the performance for the fine-tuning on imagenet.
Now here is the result:

The train/pose_loss is already lower to 0.03 (you mentioned in the previous post) after 140k iterations, but the test/mPCP is around 0.47. Will wait and see whether it will achieve 0.55
By the way, will the program converge every time?

[asanakoy]

You need to train longer. Should converge