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Models/Panoptic FCN* (Swin-L, single-scale)

Panoptic FCN* (Swin-L, single-scale)

Reported on 30 benchmarks across 3 tasks · 1 paper · 30 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Medical10 results

Semantic SegmentationonMapillary val
PQ· 2020-12-01
45.7
best: 46.7 (OneFormer (DiNAT-L, single-scale))
SOTA
Fully Convolutional Networks for Panoptic Segmentation arXiv:2012.00720
Semantic SegmentationonMapillary val
PQst· 2020-12-01
52.1
best: 54.9 (OneFormer (DiNAT-L, single-scale))
SOTA
Fully Convolutional Networks for Panoptic Segmentation arXiv:2012.00720
Semantic SegmentationonMapillary val
PQth· 2020-12-01
40.8
SOTA
Fully Convolutional Networks for Panoptic Segmentation arXiv:2012.00720
Semantic SegmentationonCOCO minival
PQth· 2020-12-01
58.5
best: 67.1 (OneFormer (InternImage-H,single-scale))
SOTA
Fully Convolutional Networks for Panoptic Segmentation arXiv:2012.00720
Semantic SegmentationonCOCO minival
RQ· 2020-12-01
61.6
best: 63.5 (MaskFormer (single-scale))
SOTA
Fully Convolutional Networks for Panoptic Segmentation arXiv:2012.00720
Semantic SegmentationonCOCO minival
RQst· 2020-12-01
51.1
SOTA
Fully Convolutional Networks for Panoptic Segmentation arXiv:2012.00720
Semantic SegmentationonCOCO minival
RQth· 2020-12-01
68.6
SOTA
Fully Convolutional Networks for Panoptic Segmentation arXiv:2012.00720
Semantic SegmentationonCOCO minival
SQ· 2020-12-01
83.2
SOTA
Fully Convolutional Networks for Panoptic Segmentation arXiv:2012.00720
Semantic SegmentationonCOCO minival
SQst· 2020-12-01
81.1
SOTA
Fully Convolutional Networks for Panoptic Segmentation arXiv:2012.00720
Semantic SegmentationonCOCO minival
SQth· 2020-12-01
84.6
SOTA
Fully Convolutional Networks for Panoptic Segmentation arXiv:2012.00720

Audio10 results

10-shot image generationonMapillary val
PQ· 2020-12-01
45.7
best: 46.7 (OneFormer (DiNAT-L, single-scale))
SOTA
Fully Convolutional Networks for Panoptic Segmentation arXiv:2012.00720
10-shot image generationonMapillary val
PQst· 2020-12-01
52.1
best: 54.9 (OneFormer (DiNAT-L, single-scale))
SOTA
Fully Convolutional Networks for Panoptic Segmentation arXiv:2012.00720
10-shot image generationonMapillary val
PQth· 2020-12-01
40.8
SOTA
Fully Convolutional Networks for Panoptic Segmentation arXiv:2012.00720
10-shot image generationonCOCO minival
PQth· 2020-12-01
58.5
best: 67.1 (OneFormer (InternImage-H,single-scale))
SOTA
Fully Convolutional Networks for Panoptic Segmentation arXiv:2012.00720
10-shot image generationonCOCO minival
RQ· 2020-12-01
61.6
best: 63.5 (MaskFormer (single-scale))
SOTA
Fully Convolutional Networks for Panoptic Segmentation arXiv:2012.00720
10-shot image generationonCOCO minival
RQst· 2020-12-01
51.1
SOTA
Fully Convolutional Networks for Panoptic Segmentation arXiv:2012.00720
10-shot image generationonCOCO minival
RQth· 2020-12-01
68.6
SOTA
Fully Convolutional Networks for Panoptic Segmentation arXiv:2012.00720
10-shot image generationonCOCO minival
SQ· 2020-12-01
83.2
SOTA
Fully Convolutional Networks for Panoptic Segmentation arXiv:2012.00720
10-shot image generationonCOCO minival
SQst· 2020-12-01
81.1
SOTA
Fully Convolutional Networks for Panoptic Segmentation arXiv:2012.00720
10-shot image generationonCOCO minival
SQth· 2020-12-01
84.6
SOTA
Fully Convolutional Networks for Panoptic Segmentation arXiv:2012.00720

Computer Vision10 results

Panoptic SegmentationonMapillary val
PQ· 2020-12-01
45.7
best: 46.7 (OneFormer (DiNAT-L, single-scale))
SOTA
Fully Convolutional Networks for Panoptic Segmentation arXiv:2012.00720
Panoptic SegmentationonMapillary val
PQst· 2020-12-01
52.1
best: 54.9 (OneFormer (DiNAT-L, single-scale))
SOTA
Fully Convolutional Networks for Panoptic Segmentation arXiv:2012.00720
Panoptic SegmentationonMapillary val
PQth· 2020-12-01
40.8
SOTA
Fully Convolutional Networks for Panoptic Segmentation arXiv:2012.00720
Panoptic SegmentationonCOCO minival
PQth· 2020-12-01
58.5
best: 67.1 (OneFormer (InternImage-H,single-scale))
SOTA
Fully Convolutional Networks for Panoptic Segmentation arXiv:2012.00720
Panoptic SegmentationonCOCO minival
RQ· 2020-12-01
61.6
best: 63.5 (MaskFormer (single-scale))
SOTA
Fully Convolutional Networks for Panoptic Segmentation arXiv:2012.00720
Panoptic SegmentationonCOCO minival
RQst· 2020-12-01
51.1
SOTA
Fully Convolutional Networks for Panoptic Segmentation arXiv:2012.00720
Panoptic SegmentationonCOCO minival
RQth· 2020-12-01
68.6
SOTA
Fully Convolutional Networks for Panoptic Segmentation arXiv:2012.00720
Panoptic SegmentationonCOCO minival
SQ· 2020-12-01
83.2
SOTA
Fully Convolutional Networks for Panoptic Segmentation arXiv:2012.00720
Panoptic SegmentationonCOCO minival
SQst· 2020-12-01
81.1
SOTA
Fully Convolutional Networks for Panoptic Segmentation arXiv:2012.00720
Panoptic SegmentationonCOCO minival
SQth· 2020-12-01
84.6
SOTA
Fully Convolutional Networks for Panoptic Segmentation arXiv:2012.00720