What are the image segmentation techniques other than U-Net, Mask-RCNN, FCN ? In there any article discussing all tecniques with their pros and cons?
Saif ul Islam
This comprehensive survey may be useful:
S. Minaee, Y. Y. Boykov, F. Porikli, A. J. Plaza, N. Kehtarnavaz and D. Terzopoulos, "Image Segmentation Using Deep Learning: A Survey," in IEEE Transactions on Pattern Analysis and Machine Intelligence, doi: 10.1109/TPAMI.2021.3059968.
You can have a look at the following paper from 2017. Though it is a little old, but the paper is detailed and might solve your purpose.
https://ieeexplore.ieee.org/document/8389420
There is another paper from 2020:
https://link.springer.com/article/10.1007/s10462-020-09830-9
Besides, if you are looking for medical image segmentation, there are quite a few survey papers:
https://link.springer.com/article/10.1007/s12065-020-00540-3
https://www.ncbi.nlm.nih.gov/pmc/articles/pmc7642729/
https://www.researchgate.net/profile/Jianhong_Cheng/publication/341826320_A_Survey_on_U-shaped_networks_in_Medical_Image_Segmentations/links/5fab45fb92851cf7dd0dd058/A-Survey-on-U-shaped-networks-in-Medical-Image-Segmentations.pdf
Hope it helps :)
you can check this article, it may help you
https://www.mdpi.com/2071-1050/13/3/1224/pdf
From a research and practical perspective, take a look at the 9 Benchmarks posted on PapersWithCode
https://paperswithcode.com/task/instance-segmentation
Currently, the leading benchmark is the Swin-Dual-B Model from the paper, CBNetV2: A Composite Backbone Network Architecture for Object Detection, Preprint CBNetV2: A Composite Backbone Network Architecture for Objec...
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