Video Polyp Segmentation on SUN-SEG-Easy (Unseen)

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Dice

Rank	Model	Dice	S measure	mean E-measure	weighted F-measure	mean F-measure	Sensitivity	mean IoU	Paper	Code	Year
1	YOLO-SAM 2	0.90	0.9	93.8	–	93.8	83.7	–	Self-Prompting Polyp Segmentation in Colonoscopy using Hybrid Yolo-SAM 2 Model	sajjad-sh33/yolo_sam2	2024
2	LGRNet	0.853	–	–	–	–	–	0.783	LGRNet: Local-Global Reciprocal Network for Uterine Fibroid Segmentation in Ultrasound Videos	bio-mlhui/lgrnet	2024
3	SALI	0.825	0.870	0.920	0.794	0.831	0.811	–	SALI: Short-term Alignment and Long-term Interaction Network for Colonoscopy Video Polyp Segmentation	Scatteredrain/SALI	2024
4	PNS+	0.756	0.806	0.798	0.676	0.730	0.630	–	Video Polyp Segmentation: A Deep Learning Perspective	DengPingFan/PraNet · DengPingFan/Inf-Net · gewelsji/vps · +1	2022
5	AutoSAM	0.753	0.815	0.855	0.716	0.774	0.672	–	AutoSAM: Adapting SAM to Medical Images by Overloading the Prompt Encoder		2023
6	2/3D	0.722	0.786	0.777	0.652	0.708	0.603	–
7	ACSNet	0.713	0.782	0.779	0.642	0.688	0.601	–
8	MAT	0.710	0.770	0.737	0.575	0.641	0.542	–	MATNet: Motion-Attentive Transition Network for Zero-Shot Video Object Segmentation	tfzhou/MATNet	2020
9	FSNet	0.702	0.725	0.695	0.551	0.630	0.493	–	Full-Duplex Strategy for Video Object Segmentation	GewelsJI/FSNet	2021
10	PNSNet	0.676	0.767	0.744	0.616	0.664	0.574	–	Progressively Normalized Self-Attention Network for Video Polyp Segmentation	gewelsji/vps · GewelsJI/PNS-Net · GewelsJI/FSNet	2021
11	SANet	0.649	0.720	0.745	0.566	0.634	0.521	–	Shallow Attention Network for Polyp Segmentation	weijun88/sanet	2021
12	PraNet	0.621	0.733	0.753	0.572	0.632	0.524	–	PraNet: Parallel Reverse Attention Network for Polyp Segmentation	DengPingFan/PraNet · GewelsJI/PNS-Net · Thehunk1206/PRANet-Polyps-Segmentation · +1	2020
13	COSNet	0.596	0.654	0.600	0.431	0.496	0.359	–	See More, Know More: Unsupervised Video Object Segmentation with Co-Attention Siamese Networks	carrierlxk/COSNet	2020
14	PCSA	0.592	0.680	0.660	0.451	0.519	0.398	–
15	DCF	0.325	0.523	0.514	0.270	0.312	0.340	–	Dynamic Context-Sensitive Filtering Network for Video Salient Object Detection	oiplab-dut/dcfnet	2021
16	AMD	0.266	0.474	0.533	0.133	0.146	0.222	–	The Emergence of Objectness: Learning Zero-Shot Segmentation from Videos	rt219/the-emergence-of-objectness	2021
17	UNet++	–	–	–	–	–	0.457	–	UNet++: A Nested U-Net Architecture for Medical Image Segmentation	qubvel/segmentation_models.pytorch · PaddlePaddle/PaddleSeg · MrGiovanni/Nested-UNet · +31	2018
18	UNet	–	–	–	–	–	0.420	–	U-Net: Convolutional Networks for Biomedical Image Segmentation	labmlai/annotated_deep_learning_paper_implementations · milesial/Pytorch-UNet · open-mmlab/mmsegmentation · +484	2015