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Video Polyp Segmentation On Sun Seg Easy

Metrics

Dice

S measure

Sensitivity

mean E-measure

mean F-measure

weighted F-measure

Results

Performance results of various models on this benchmark

Model Name	Dice	S measure	Sensitivity	mean E-measure	mean F-measure	weighted F-measure	Paper Title	Repository
PNSNet	0.676	0.767	0.574	0.744	0.664	0.616	Progressively Normalized Self-Attention Network for Video Polyp Segmentation
YOLO-SAM 2	0.90	0.9	83.7	93.8	93.8	-	Self-Prompting Polyp Segmentation in Colonoscopy using Hybrid Yolo-SAM 2 Model
FSNet	0.702	0.725	0.493	0.695	0.630	0.551	Full-Duplex Strategy for Video Object Segmentation
ACSNet	0.713	0.782	0.601	0.779	0.688	0.642	-	-
UNet	-	-	0.420	-	-	-	U-Net: Convolutional Networks for Biomedical Image Segmentation
LGRNet	0.853	-	-	-	-	-	LGRNet: Local-Global Reciprocal Network for Uterine Fibroid Segmentation in Ultrasound Videos	-
DCF	0.325	0.523	0.340	0.514	0.312	0.270	Dynamic Context-Sensitive Filtering Network for Video Salient Object Detection	-
COSNet	0.596	0.654	0.359	0.600	0.496	0.431	See More, Know More: Unsupervised Video Object Segmentation with Co-Attention Siamese Networks
PNS+	0.756	0.806	0.630	0.798	0.730	0.676	Video Polyp Segmentation: A Deep Learning Perspective
MAT	0.710	0.770	0.542	0.737	0.641	0.575	MATNet: Motion-Attentive Transition Network for Zero-Shot Video Object Segmentation
AutoSAM	0.753	0.815	0.672	0.855	0.774	0.716	AutoSAM: Adapting SAM to Medical Images by Overloading the Prompt Encoder	-
SANet	0.649	0.720	0.521	0.745	0.634	0.566	Shallow Attention Network for Polyp Segmentation
PCSA	0.592	0.680	0.398	0.660	0.519	0.451	-	-
UNet++	-	-	0.457	-	-	-	UNet++: A Nested U-Net Architecture for Medical Image Segmentation
PraNet	0.621	0.733	0.524	0.753	0.632	0.572	PraNet: Parallel Reverse Attention Network for Polyp Segmentation
2/3D	0.722	0.786	0.603	0.777	0.708	0.652	-	-
AMD	0.266	0.474	0.222	0.533	0.146	0.133	The Emergence of Objectness: Learning Zero-Shot Segmentation from Videos
SALI	0.825	0.870	0.811	0.920	0.831	0.794	SALI: Short-term Alignment and Long-term Interaction Network for Colonoscopy Video Polyp Segmentation

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