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COCO test-dev
Semantic Segmentation on COCO test-dev
Metric: PQ (higher is better)
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Model name (A→Z)
#
Model
↕
PQ
▼
Extra Data
Paper
Date
↕
Code
1
Mask DINO (single scale)
59.5
No
Mask DINO: Towards A Unified Transformer-based F...
2022-06-06
Code
2
kMaX-DeepLab (single-scale)
58.5
No
kMaX-DeepLab: k-means Mask Transformer
2022-07-08
Code
3
Mask2Former (Swin-L)
58.3
No
Masked-attention Mask Transformer for Universal ...
2021-12-02
Code
4
Panoptic SegFormer (Swin-L)
56.2
No
Panoptic SegFormer: Delving Deeper into Panoptic...
2021-09-08
Code
5
Panoptic SegFormer (PVTv2-B5)
55.8
No
Panoptic SegFormer: Delving Deeper into Panoptic...
2021-09-08
Code
6
CMT-DeepLab (single-scale)
55.7
No
CMT-DeepLab: Clustering Mask Transformers for Pa...
2022-06-17
Code
7
K-Net (Swin-L)
55.2
No
K-Net: Towards Unified Image Segmentation
2021-06-28
Code
8
MaskConver (ResNet50, single-scale)
53.6
No
MaskConver: Revisiting Pure Convolution Model fo...
2023-12-11
Code
9
MaskFormer (Swin-L)
53.3
No
Per-Pixel Classification is Not All You Need for...
2021-07-13
Code
10
Panoptic FCN* (Swin-L)
52.7
No
Fully Convolutional Networks for Panoptic Segmen...
2020-12-01
Code
11
REFINE (ResNeXt-101-DCN)
51.5
No
-
-
-
12
MaX-DeepLab-L (single-scale)
51.3
No
MaX-DeepLab: End-to-End Panoptic Segmentation wi...
2020-12-01
Code
13
Panoptic SegFormer (ResNet-101)
50.9
No
Panoptic SegFormer: Delving Deeper into Panoptic...
2021-09-08
Code
14
Panoptic SegFormer (ResNet-50)
50.2
No
Panoptic SegFormer: Delving Deeper into Panoptic...
2021-09-08
Code
15
DetectoRS (ResNeXt-101-64x4d, multi-scale)
50
No
DetectoRS: Detecting Objects with Recursive Feat...
2020-06-03
Code
16
REFINE (ResNet-101-DCN)
49.6
No
-
-
-
17
SpatialFlow(ResNet-101-FPN)
48.5
No
SpatialFlow: Bridging All Tasks for Panoptic Seg...
2019-10-19
Code
18
Ada-Segment (ResNet-101-DCN)
48.5
No
Ada-Segment: Automated Multi-loss Adaptation for...
2020-12-07
-
19
K-Net (R101-FPN-DCN)
48.3
No
K-Net: Towards Unified Image Segmentation
2021-06-28
Code
20
SOGNet (ResNet-101-FPN)
47.8
No
SOGNet: Scene Overlap Graph Network for Panoptic...
2019-11-18
Code
21
Panoptic FCN*++ (DCN-101-FPN)
47.5
No
Fully Convolutional Networks for Panoptic Segmen...
2020-12-01
Code
22
UPSNet (ResNet-101-FPN)
46.6
No
UPSNet: A Unified Panoptic Segmentation Network
2019-01-12
Code
23
OCFusion (ResNeXt-101-FPN)
46.6
No
Learning Instance Occlusion for Panoptic Segment...
2019-06-13
Code
24
Panoptic-DeepLab (SWideRNet-[1, 1, 4], multi-scale)
46.5
No
Scaling Wide Residual Networks for Panoptic Segm...
2020-11-23
-
25
AUNet (ResNext-152-FPN)
46.5
No
Attention-guided Unified Network for Panoptic Se...
2018-12-10
-
26
AUNet (ResNet-152-FPN)
45.5
No
Attention-guided Unified Network for Panoptic Se...
2018-12-10
-
27
AUNet (ResNet-101-FPN)
45.2
No
Attention-guided Unified Network for Panoptic Se...
2018-12-10
-
28
Axial-DeepLab-L (multi-scale)
44.2
No
Axial-DeepLab: Stand-Alone Axial-Attention for P...
2020-03-17
Code
29
Axial-DeepLab-L
43.6
No
Axial-DeepLab: Stand-Alone Axial-Attention for P...
2020-03-17
Code
30
AdaptIS (ResNeXt-101)
42.8
No
AdaptIS: Adaptive Instance Selection Network
2019-09-17
-
31
Panoptic-DeepLab (Xception-71)
41.4
No
Panoptic-DeepLab: A Simple, Strong, and Fast Bas...
2019-11-22
Code
32
Panoptic FPN
40.9
No
Panoptic Feature Pyramid Networks
2019-01-08
Code
33
TASCNet
40.7
No
Learning to Fuse Things and Stuff
2018-12-04
-
34
EPSNet (ResNet-101-FPN)
38.9
No
EPSNet: Efficient Panoptic Segmentation Network ...
2020-03-23
Code
35
COPS (ResNet-50)
38.5
No
Combinatorial Optimization for Panoptic Segmenta...
2021-06-06
Code
36
PCV (ResNet-50)
37.7
No
Pixel Consensus Voting for Panoptic Segmentation
2020-04-04
-
37
GES Net
33.7
No
Generator evaluator-selector net for panoptic im...
2019-08-24
Code
38
JSIS-Net
27.2
No
Panoptic Segmentation with a Joint Semantic and ...
2018-09-06
-
#1
Mask DINO (single scale)
SOTA
59.5
PQ
· 2022-06-06
Mask DINO: Towards A Unified Transformer-based Framework for Object Detection and Segmentation
Code
#2
kMaX-DeepLab (single-scale)
58.5
PQ
· 2022-07-08
kMaX-DeepLab: k-means Mask Transformer
Code
#3
Mask2Former (Swin-L)
SOTA
58.3
PQ
· 2021-12-02
Masked-attention Mask Transformer for Universal Image Segmentation
Code
#4
Panoptic SegFormer (Swin-L)
SOTA
56.2
PQ
· 2021-09-08
Panoptic SegFormer: Delving Deeper into Panoptic Segmentation with Transformers
Code
#5
Panoptic SegFormer (PVTv2-B5)
55.8
PQ
· 2021-09-08
Panoptic SegFormer: Delving Deeper into Panoptic Segmentation with Transformers
Code
#6
CMT-DeepLab (single-scale)
55.7
PQ
· 2022-06-17
CMT-DeepLab: Clustering Mask Transformers for Panoptic Segmentation
Code
#7
K-Net (Swin-L)
SOTA
55.2
PQ
· 2021-06-28
K-Net: Towards Unified Image Segmentation
Code
#8
MaskConver (ResNet50, single-scale)
53.6
PQ
· 2023-12-11
MaskConver: Revisiting Pure Convolution Model for Panoptic Segmentation
Code
#9
MaskFormer (Swin-L)
53.3
PQ
· 2021-07-13
Per-Pixel Classification is Not All You Need for Semantic Segmentation
Code
#10
Panoptic FCN* (Swin-L)
SOTA
52.7
PQ
· 2020-12-01
Fully Convolutional Networks for Panoptic Segmentation
Code
#11
REFINE (ResNeXt-101-DCN)
51.5
PQ
No paper
#12
MaX-DeepLab-L (single-scale)
51.3
PQ
· 2020-12-01
MaX-DeepLab: End-to-End Panoptic Segmentation with Mask Transformers
Code
#13
Panoptic SegFormer (ResNet-101)
50.9
PQ
· 2021-09-08
Panoptic SegFormer: Delving Deeper into Panoptic Segmentation with Transformers
Code
#14
Panoptic SegFormer (ResNet-50)
50.2
PQ
· 2021-09-08
Panoptic SegFormer: Delving Deeper into Panoptic Segmentation with Transformers
Code
#15
DetectoRS (ResNeXt-101-64x4d, multi-scale)
SOTA
50
PQ
· 2020-06-03
DetectoRS: Detecting Objects with Recursive Feature Pyramid and Switchable Atrous Convolution
Code
#16
REFINE (ResNet-101-DCN)
49.6
PQ
No paper
#17
SpatialFlow(ResNet-101-FPN)
SOTA
48.5
PQ
· 2019-10-19
SpatialFlow: Bridging All Tasks for Panoptic Segmentation
Code
#18
Ada-Segment (ResNet-101-DCN)
48.5
PQ
· 2020-12-07
Ada-Segment: Automated Multi-loss Adaptation for Panoptic Segmentation
#19
K-Net (R101-FPN-DCN)
48.3
PQ
· 2021-06-28
K-Net: Towards Unified Image Segmentation
Code
#20
SOGNet (ResNet-101-FPN)
47.8
PQ
· 2019-11-18
SOGNet: Scene Overlap Graph Network for Panoptic Segmentation
Code
#21
Panoptic FCN*++ (DCN-101-FPN)
47.5
PQ
· 2020-12-01
Fully Convolutional Networks for Panoptic Segmentation
Code
#22
UPSNet (ResNet-101-FPN)
SOTA
46.6
PQ
· 2019-01-12
UPSNet: A Unified Panoptic Segmentation Network
Code
#23
OCFusion (ResNeXt-101-FPN)
46.6
PQ
· 2019-06-13
Learning Instance Occlusion for Panoptic Segmentation
Code
#24
Panoptic-DeepLab (SWideRNet-[1, 1, 4], multi-scale)
46.5
PQ
· 2020-11-23
Scaling Wide Residual Networks for Panoptic Segmentation
#25
AUNet (ResNext-152-FPN)
SOTA
46.5
PQ
· 2018-12-10
Attention-guided Unified Network for Panoptic Segmentation
#26
AUNet (ResNet-152-FPN)
45.5
PQ
· 2018-12-10
Attention-guided Unified Network for Panoptic Segmentation
#27
AUNet (ResNet-101-FPN)
45.2
PQ
· 2018-12-10
Attention-guided Unified Network for Panoptic Segmentation
#28
Axial-DeepLab-L (multi-scale)
44.2
PQ
· 2020-03-17
Axial-DeepLab: Stand-Alone Axial-Attention for Panoptic Segmentation
Code
#29
Axial-DeepLab-L
43.6
PQ
· 2020-03-17
Axial-DeepLab: Stand-Alone Axial-Attention for Panoptic Segmentation
Code
#30
AdaptIS (ResNeXt-101)
42.8
PQ
· 2019-09-17
AdaptIS: Adaptive Instance Selection Network
#31
Panoptic-DeepLab (Xception-71)
41.4
PQ
· 2019-11-22
Panoptic-DeepLab: A Simple, Strong, and Fast Baseline for Bottom-Up Panoptic Segmentation
Code
#32
Panoptic FPN
40.9
PQ
· 2019-01-08
Panoptic Feature Pyramid Networks
Code
#33
TASCNet
SOTA
40.7
PQ
· 2018-12-04
Learning to Fuse Things and Stuff
#34
EPSNet (ResNet-101-FPN)
38.9
PQ
· 2020-03-23
EPSNet: Efficient Panoptic Segmentation Network with Cross-layer Attention Fusion
Code
#35
COPS (ResNet-50)
38.5
PQ
· 2021-06-06
Combinatorial Optimization for Panoptic Segmentation: A Fully Differentiable Approach
Code
#36
PCV (ResNet-50)
37.7
PQ
· 2020-04-04
Pixel Consensus Voting for Panoptic Segmentation
#37
GES Net
33.7
PQ
· 2019-08-24
Generator evaluator-selector net for panoptic image segmentation and splitting unfamiliar objects into parts
Code
#38
JSIS-Net
SOTA
27.2
PQ
· 2018-09-06
Panoptic Segmentation with a Joint Semantic and Instance Segmentation Network