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boyetosekuji t1_ixnhgzt wrote

Have you run into any use cases where bg removal suffers?

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swdsld OP t1_ixnicaw wrote

We also have some problem with detecting all object in the given image. It is quite common problem for salient object detection because objects in the the dataset are usually center-biased. It could be our next research topic!

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boyetosekuji t1_ixnqtst wrote

What's the reason for the smoke effect https://imgur.com/a/GGdWIig instead of sharp outline? Open in new tab (white bg)

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swdsld OP t1_ixou56r wrote

Thank you for letting me know about the problem. It's actually quite common in those kind of background removal tools. When the model is not sure whether the region is a part of salient object or not, it produces such artifacts. It could happen for both our method and other companies' tool. We can avoid that problem by training the model with various scenes which is what I'm planning to in the future release.

Tools like remove.bg or Apple's native tool are provided commercially, so they must have been using massive dataset including their privately annotated ground truths. We don't think that we can outperform in every scenario than theirs, but I'm trying my best training my method with the datasets which are available for me now.

Stay tuned for the future updates!

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boyetosekuji t1_ixovllt wrote

i've got some good images with your tool, this one was not bad too, aesthetically. Would implementing depth map work? although it would add another GPU intensive task. Keep going, Good luck.

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swdsld OP t1_ixoxfyf wrote

Using depth map would definitely be a great option. Thank you for your kind comment!

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boyetosekuji t1_ixoywrk wrote

if you want to check depth map take a look at this paper, they claim better edge detection, valuable for eg. the wires of san Francisco bridge, etc

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