Instance Segmentation Models

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Instance Segmentation models are models that perform the task of Instance Segmentation.

Methods

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Method	Year	Papers
Mask R-CNN Mask R-CNN	2017	319
HTC Hybrid Task Cascade for Instance Segmentation	2019	21
Cascade Mask R-CNN Cascade R-CNN: Delving into High Quality Object Detection	2017	16
GCNet GCNet: Non-local Networks Meet Squeeze-Excitation Networks and Beyond	2019	9
PANet Path Aggregation Network for Instance Segmentation	2018	9
CPN Contour Proposal Networks for Biomedical Instance Segmentation	2021	8
CondInst Conditional Convolutions for Instance Segmentation	2020	5
CenterMask CenterMask : Real-Time Anchor-Free Instance Segmentation	2019	4
VisTR End-to-End Video Instance Segmentation with Transformers	2020	3
K-Net K-Net: Towards Unified Image Segmentation	2021	3
SCNet SCNet: Training Inference Sample Consistency for Instance Segmentation	2020	2
BlendMask BlendMask: Top-Down Meets Bottom-Up for Instance Segmentation	2020	2
Mask Scoring R-CNN Mask Scoring R-CNN	2019	1
Deep-MAC The surprising impact of mask-head architecture on novel class segmentation	2021	1
AffCorrs	2000	1