Segmentation performance is too different compared with the paper.

[oorrppp2]

Firstly, I appreciate for your release of the pytorch code.
I just succeeded running the code, and I get the clear predicted labels through feeding the example images in 'data/demo/*color.png' as input.

But when I run the script demo.sh with ycb video dataset image, I couldn't get the clear predicted labels.
It was creating a label that looked like a superpixel for a background that is not a target object.
It was different compared with the paper or YouTube (https://www.youtube.com/watch?v=B7I7R1GdzV8).

I run the demo.sh, and print out predicted labels.
I wonder it is right.

How can I get the clear segmentation with YCB video dataset like yours?
I used 'ycb_object', 'ycb_video' models, and all of them were bad.

Thank you!
Regard,

[Yu Xiang]

I am not sure what is wrong, but these results are not correct. Make sure you used the checkpoints in the folder 'ycb_video', and also check the script experiments/scripts/ycb_video_test.sh for testing on ycb video.