Hi,
Is there any single-stage deep learning based instance segmentation method that outputs single channel mask where each pixel indicates instance labels (assume we are considering one class: person)?
To be more concise, Is it possible that I have an input image with multiple instances of a person class and deep learning model outputs a mask for all instances present in input image by predicting 1,... k labels in single channel output mask
I hope my question is clear now
this link may be help you
https://www.mathworks.com/help/vision/ug/semantic-segmentation-using-deep-learning.html;jsessionid=614d85cdfe6bcccaccb4697a08ee
Hi Mehwish,
Following two articles will answer your question.
1. https://arxiv.org/pdf/1912.01176.pdf
2. https://openaccess.thecvf.com/content_CVPR_2019/papers/Fan_S4Net_Single_Stage_Salient-Instance_Segmentation_CVPR_2019_paper.pdf
Related to your query, I suggest you to follow https://towardsdatascience.com/single-stage-instance-segmentation-a-review-1eeb66e0cc49
https://towardsdatascience.com/review-deepmask-instance-segmentation-30327a072339
https://arxiv.org/pdf/2001.05566.pdf
https://openaccess.thecvf.com/content_cvpr_2017/papers/Bai_Deep_Watershed_Transform_CVPR_2017_paper.pdf
Yes it is possible, I guess I have tried the same thing with U-net. but I don't know for some reason when the number of classes increases the model accuracy drops. but I assume for one class should be working fine.
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