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SOTA
全景分割
Panoptic Segmentation On Coco Test Dev
Panoptic Segmentation On Coco Test Dev
评估指标
PQ
PQst
PQth
评测结果
各个模型在此基准测试上的表现结果
Columns
模型名称
PQ
PQst
PQth
Paper Title
Repository
Mask DINO (single scale)
59.5
-
-
Mask DINO: Towards A Unified Transformer-based Framework for Object Detection and Segmentation
kMaX-DeepLab (single-scale)
58.5
49.0
64.8
kMaX-DeepLab: k-means Mask Transformer
Mask2Former (Swin-L)
58.3
48.1
65.1
Masked-attention Mask Transformer for Universal Image Segmentation
Panoptic SegFormer (Swin-L)
56.2
47.0
62.3
Panoptic SegFormer: Delving Deeper into Panoptic Segmentation with Transformers
Panoptic SegFormer (PVTv2-B5)
55.8
46.5
61.9
Panoptic SegFormer: Delving Deeper into Panoptic Segmentation with Transformers
CMT-DeepLab (single-scale)
55.7
46.8
61.6
CMT-DeepLab: Clustering Mask Transformers for Panoptic Segmentation
K-Net (Swin-L)
55.2
46.2
61.2
K-Net: Towards Unified Image Segmentation
MaskConver (ResNet50, single-scale)
53.6
58.9
45.6
MaskConver: Revisiting Pure Convolution Model for Panoptic Segmentation
MaskFormer (Swin-L)
53.3
44.5
59.1
Per-Pixel Classification is Not All You Need for Semantic Segmentation
Panoptic FCN* (Swin-L)
52.7
-
59.4
Fully Convolutional Networks for Panoptic Segmentation
REFINE (ResNeXt-101-DCN)
51.5
39.2
59.6
REFINE: Prediction Fusion Network for Panoptic Segmentation
-
MaX-DeepLab-L (single-scale)
51.3
42.4
57.2
MaX-DeepLab: End-to-End Panoptic Segmentation with Mask Transformers
Panoptic SegFormer (ResNet-101)
50.9
43.0
56.2
Panoptic SegFormer: Delving Deeper into Panoptic Segmentation with Transformers
Panoptic SegFormer (ResNet-50)
50.2
42.4
55.3
Panoptic SegFormer: Delving Deeper into Panoptic Segmentation with Transformers
DetectoRS (ResNeXt-101-64x4d, multi-scale)
50
37.2
58.5
DetectoRS: Detecting Objects with Recursive Feature Pyramid and Switchable Atrous Convolution
REFINE (ResNet-101-DCN)
49.6
37.7
57.5
REFINE: Prediction Fusion Network for Panoptic Segmentation
-
Ada-Segment (ResNet-101-DCN)
48.5
37.6
55.7
Ada-Segment: Automated Multi-loss Adaptation for Panoptic Segmentation
-
SpatialFlow(ResNet-101-FPN)
48.5
37.9
55.5
SpatialFlow: Bridging All Tasks for Panoptic Segmentation
K-Net (R101-FPN-DCN)
48.3
39.7
54
K-Net: Towards Unified Image Segmentation
SOGNet (ResNet-101-FPN)
47.8
-
-
SOGNet: Scene Overlap Graph Network for Panoptic Segmentation
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