Semantic Segmentation on Mapillary val

Metric: PQth (higher is better)

LeaderboardDataset

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#	Model↕	PQth▼	Extra Data	Paper	Date↕	Code
1	Panoptic FCN* (Swin-L, single-scale)	40.8	No	Fully Convolutional Networks for Panoptic Segmen...	2020-12-01	Code
2	OneFormer (ConvNeXt-L, single-scale)	40.6	No	OneFormer: One Transformer to Rule Universal Ima...	2022-11-10	Code
3	OneFormer (DiNAT-L, single-scale)	40.5	No	OneFormer: One Transformer to Rule Universal Ima...	2022-11-10	Code
4	Panoptic-DeepLab (SWideRNet-(1, 1, 4.5), multi-scale)	39.3	No	Scaling Wide Residual Networks for Panoptic Segm...	2020-11-23	-
5	Mask2Former + Intra-Batch Supervision (ResNet-50)	34.9	No	Intra-Batch Supervision for Panoptic Segmentatio...	2023-04-17	Code
6	Axial-DeepLab-L (multi-scale)	33.4	No	Axial-DeepLab: Stand-Alone Axial-Attention for P...	2020-03-17	Code
7	Panoptic FCN* (ResNet-FPN)	32.9	No	Fully Convolutional Networks for Panoptic Segmen...	2020-12-01	Code

#1Panoptic FCN* (Swin-L, single-scale)SOTA
40.8
PQth· 2020-12-01
Fully Convolutional Networks for Panoptic Segmentation Code
#2OneFormer (ConvNeXt-L, single-scale)
40.6
PQth· 2022-11-10
OneFormer: One Transformer to Rule Universal Image Segmentation Code
#3OneFormer (DiNAT-L, single-scale)
40.5
PQth· 2022-11-10
OneFormer: One Transformer to Rule Universal Image Segmentation Code
#4Panoptic-DeepLab (SWideRNet-(1, 1, 4.5), multi-scale)SOTA
39.3
PQth· 2020-11-23
Scaling Wide Residual Networks for Panoptic Segmentation
#5Mask2Former + Intra-Batch Supervision (ResNet-50)
34.9
PQth· 2023-04-17
Intra-Batch Supervision for Panoptic Segmentation on High-Resolution Images Code
#6Axial-DeepLab-L (multi-scale)SOTA
33.4
PQth· 2020-03-17
Axial-DeepLab: Stand-Alone Axial-Attention for Panoptic Segmentation Code
#7Panoptic FCN* (ResNet-FPN)
32.9
PQth· 2020-12-01
Fully Convolutional Networks for Panoptic Segmentation Code