Video Polyp Segmentation on SUN-SEG Easy (Unseen)

87S-alpha ScoreSALI

Evaluation results

Method
SALI2024.06	87	92	79.4	83.1	0.825	0.811	—	—
SLT-Net2024.06	84.8	89.3	77.5	81.7	0.792	0.747	—	—
MAST2024.06	84.5	89.8	77	81.9	0.784	0.755	—	—
PNS+2024.06	80.6	79.8	67.6	73	0.756	0.63	—	—
PNS+2026.06	80.6	79.8	67.6	—	0.678	—	0.591	4.4
2/3D2024.06	78.6	77.7	65.2	70.8	0.722	0.603	—	—
ARTEMIS2026.06	78.6	79.7	65.9	—	0.667	—	0.587	4.3
PraNet2026.06	78.1	78.8	66.3	—	0.665	—	0.582	5.2
SEE2026.06	77.8	78.8	53.3	—	0.658	—	0.562	10.2
WS-SAM2026.06	77.1	78.5	50.6	—	0.644	—	0.552	9.2
ARTEMIS2026.06	77	76.9	52.9	—	0.628	—	0.539	8
PNS-Net2024.06	76.7	74.4	61.6	66.4	0.676	0.574	—	—
PNS2026.06	76.7	74.4	61.6	—	0.618	—	0.545	4.8
ProMaC2026.06	75.2	76.1	49.4	—	0.626	—	0.523	12.7
WeakPolyp2026.06	75.1	76.8	47.3	—	0.632	—	0.536	12.6
ProMaC2026.06	74.9	77.4	51.3	—	0.648	—	0.558	12.8
WS-SAM2026.06	74.5	76	45.4	—	0.62	—	0.526	12
SEE2026.06	74.5	75.6	47.1	—	0.621	—	0.526	12.4
SCOD2026.06	74.2	75.8	45.1	—	0.617	—	0.52	12.6
SCWS2026.06	73.6	74.2	44.5	—	0.603	—	0.504	13.5
TEL2026.06	72.9	74.3	42.2	—	0.613	—	0.517	14.3
GenSAM2026.06	72.7	74.3	42.2	—	0.609	—	0.51	14.3
GenSAM2026.06	72.7	75.4	42.4	—	0.619	—	0.519	14.3
FLA-Net2024.06	72.2	69.7	54.7	59.7	0.636	0.506	—	—
TEL2026.06	72.2	72.9	43.9	—	0.597	—	0.505	15.2
SCOD2026.06	71.7	73.2	40.5	—	0.602	—	0.505	15.4
SCWS2026.06	70.3	71.2	37.7	—	0.575	—	0.474	15.7
SAM-WS2026.06	66.8	68.9	32.3	—	0.567	—	0.465	19.8
SAM-WS2026.06	60.3	54.6	23.4	—	0.388	—	0.289	23.7
YOLO-SAM 22024.09	0.9	0.938	—	0.938	0.9	0.837	—	—
SLT-Net2024.09	0.848	0.893	—	0.817	0.792	0.747	—	—
DALA2026.06	0.837	0.854	0.722	0.772	0.768	0.721	—	—
Temporally Consistent Learning Framework2026.06	0.816	0.882	0.738	0.784	0.746	0.719	—	—
PNS+2022.03	0.806	0.798	0.676	0.73	0.756	0.63	—	—
PNS+2024.09	0.806	0.798	—	0.73	0.756	0.63	—	—
SSTAN2026.06	0.805	0.838	0.691	0.745	0.726	0.662	—	—
MSRF-Net2026.06	0.794	0.78	0.652	0.693	0.701	0.6	—	—
2/3D2022.03	0.786	0.777	0.652	0.708	0.722	0.603	—	—
2/3D2024.09	0.786	0.777	—	0.708	0.722	0.603	—	—
ACSNet2022.03	0.782	0.779	0.642	0.688	0.713	0.601	—	—
ACSNet2026.06	0.782	0.779	0.642	0.688	0.713	0.601	—	—
ColonSegNet2026.06	0.776	0.768	0.621	0.666	0.683	0.594	—	—
MAT2022.03	0.77	0.737	0.575	0.641	0.71	0.542	—	—
TransNetR2026.06	0.768	0.768	0.648	0.694	0.642	0.592	—	—
PNSNet2022.03	0.767	0.744	0.616	0.664	0.676	0.574	—	—
PNS-Net2024.09	0.767	0.744	—	0.664	0.676	0.574	—	—
PraNet2022.03	0.733	0.753	0.572	0.632	0.621	0.524	—	—
PraNet2026.06	0.733	0.753	0.572	0.632	0.621	0.524	—	—
FSNet2022.03	0.725	0.695	0.551	0.63	0.702	0.493	—	—
FLA-Net2024.09	0.722	0.697	—	0.597	0.636	0.506	—	—
FLA-Net2026.06	0.722	0.697	0.547	0.597	0.636	0.506	—	—
SANet2022.03	0.72	0.745	0.566	0.634	0.649	0.521	—	—
MedNeXt2026.06	0.703	0.719	0.553	0.598	0.591	0.506	—	—
UNet++2022.03	0.684	0.687	0.491	0.553	0.559	0.457	—	—
U-Net++2026.06	0.684	0.687	0.491	0.553	0.559	0.457	—	—
PCSA2022.03	0.68	0.66	0.451	0.519	0.592	0.398	—	—
UNet2022.03	0.669	0.677	0.459	0.528	0.53	0.42	—	—
U-Net2026.06	0.669	0.677	0.459	0.528	0.53	0.42	—	—
COSNet2022.03	0.654	0.6	0.431	0.496	0.596	0.359	—	—
DCF2022.03	0.523	0.514	0.27	0.312	0.325	0.34	—	—
AMD2022.03	0.474	0.533	0.133	0.146	0.266	0.222	—	—