Instance Segmentation on Freight Trains Dataset benchmark leaderboard · SOTA2 Research

Instance Segmentation on Freight Trains Dataset

74.2AP (Mask)SAM FTI-FDet

Evaluation Results

Method	Links
SAM FTI-FDet2026.03		74.2	94.8	79.9	148.2	244	16	36.3
Mask2Former2026.03		73.8	93	79.3	739.5	252	12.8	49
SAM FTI-FDet-PF2026.03		72.9	93.8	79.5	80.4	196	24.4	30.1
Mask2Former2026.03		72.6	93.3	78.9	665.2	245	13	46.3
CondInst2026.03		72.6	94.9	78.8	293.4	258	30.6	68.3
FastSAM2026.03		72	95.1	77.9	141.6	443	9.1	72
SAM-seg2026.03		71.9	94.7	77.4	450.2	411	8.6	97.2
RSPrompter-query2026.03		71.9	93.2	77.8	303.3	425	7.1	131
PointRend2026.03		71.8	95	79.1	688.2	198	30.1	65.3
PointRend2026.03		71.3	94.2	78.4	431.6	186	38.1	56.4
Mask R-CNN2026.03		70.7	93.7	77.9	336.4	234	44.6	44
Mask R-CNN2026.03		70.5	95.3	76.8	549	241	36.4	47.5
RTMDet2026.03		70.3	94.4	75.3	1,790.6	323	25.6	86.6
SOLOv22026.03		69.8	93.8	76.8	353.9	283	33.7	46.3
RTMDet2026.03		68.8	94	74.8	436	120	23.1	32.5
YOLACT2026.03		68.4	93	76	272	337	42.8	31.4
CondInst2026.03		67.3	92.8	73.3	272	250	27.1	48.2
SOLOv22026.03		67	94.4	75.8	380.6	312	28.3	49.7
QueryInst2026.03		66.8	94.5	77.5	1,986.6	263	16	62.5
YOLACT2026.03		66.6	92.7	74.3	275.4	282	31.6	50.2
SparseInst2026.03		66.5	87.9	72.2	399.8	221	76.3	47.9
SAM-det2026.03		58.9	84.5	67.9	528	233	10.2	106.7