Video Polyp Segmentation
14 papers with code • 5 benchmarks • 4 datasets
Benchmarks
These leaderboards are used to track progress in Video Polyp Segmentation
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Libraries
Use these libraries to find Video Polyp Segmentation models and implementations
STARE
SUN-SEG-Easy (Unseen)
Most implemented papers
U-Net: Convolutional Networks for Biomedical Image Segmentation
labmlai/annotated_deep_learning_paper_implementations
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There is large consent that successful training of deep networks requires many thousand annotated training samples.
UNet++: A Nested U-Net Architecture for Medical Image Segmentation
Implementation of different kinds of Unet Models for Image Segmentation - Unet , RCNN-Unet, Attention Unet, RCNN-Attention Unet, Nested Unet
PraNet: Parallel Reverse Attention Network for Polyp Segmentation
To address these challenges, we propose a parallel reverse attention network (PraNet) for accurate polyp segmentation in colonoscopy images.
Video Polyp Segmentation: A Deep Learning Perspective
We present the first comprehensive video polyp segmentation (VPS) study in the deep learning era.
Progressively Normalized Self-Attention Network for Video Polyp Segmentation
gewelsji/vps
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Existing video polyp segmentation (VPS) models typically employ convolutional neural networks (CNNs) to extract features.
Polyp-SAM++: Can A Text Guided SAM Perform Better for Polyp Segmentation?
RisabBiswas/Polyp-SAM-PlusPlus
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In the field of medical image segmentation, polyp segmentation holds a position of high importance, thus creating a model which is robust and precise is quite challenging.
See More, Know More: Unsupervised Video Object Segmentation with Co-Attention Siamese Networks
carrierlxk/COSNet
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CVPR 2019
We introduce a novel network, called CO-attention Siamese Network (COSNet), to address the unsupervised video object segmentation task from a holistic view.
MATNet: Motion-Attentive Transition Network for Zero-Shot Video Object Segmentation
tfzhou/MATNet
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IEEE Transactions on Image Processing 2020
To further demonstrate the generalization ability of our spatiotemporal learning framework, we extend MATNet to another relevant task: dynamic visual attention prediction (DVAP).
Dynamic Context-Sensitive Filtering Network for Video Salient Object Detection
oiplab-dut/dcfnet
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ICCV 2021
Our bidirectional dynamic fusion strategy encourages the interaction of spatial and temporal information in a dynamic manner.
Shallow Attention Network for Polyp Segmentation
weijun88/sanet
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To address the above issues, we propose the Shallow Attention Network (SANet) for polyp segmentation.
