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Models/Axial-DeepLab-L (single-scale)

Axial-DeepLab-L (single-scale)

Reported on 9 benchmarks across 3 tasks · 1 paper

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

Medical3 results

Semantic SegmentationonCOCO minival
PQ· 2020-03-17
43.4
best: 61.2 (HyperSeg (Swin-B))
Axial-DeepLab: Stand-Alone Axial-Attention for Panoptic Segmentation arXiv:2003.07853
Semantic SegmentationonCOCO minival
PQst· 2020-03-17
35.6
best: 49.2 (OneFormer (InternImage-H,single-scale))
Axial-DeepLab: Stand-Alone Axial-Attention for Panoptic Segmentation arXiv:2003.07853
Semantic SegmentationonCOCO minival
PQth· 2020-03-17
48.5
best: 67.1 (OneFormer (InternImage-H,single-scale))
Axial-DeepLab: Stand-Alone Axial-Attention for Panoptic Segmentation arXiv:2003.07853

Audio3 results

10-shot image generationonCOCO minival
PQ· 2020-03-17
43.4
best: 61.2 (HyperSeg (Swin-B))
Axial-DeepLab: Stand-Alone Axial-Attention for Panoptic Segmentation arXiv:2003.07853
10-shot image generationonCOCO minival
PQst· 2020-03-17
35.6
best: 49.2 (OneFormer (InternImage-H,single-scale))
Axial-DeepLab: Stand-Alone Axial-Attention for Panoptic Segmentation arXiv:2003.07853
10-shot image generationonCOCO minival
PQth· 2020-03-17
48.5
best: 67.1 (OneFormer (InternImage-H,single-scale))
Axial-DeepLab: Stand-Alone Axial-Attention for Panoptic Segmentation arXiv:2003.07853

Computer Vision3 results

Panoptic SegmentationonCOCO minival
PQ· 2020-03-17
43.4
best: 61.2 (HyperSeg (Swin-B))
Axial-DeepLab: Stand-Alone Axial-Attention for Panoptic Segmentation arXiv:2003.07853
Panoptic SegmentationonCOCO minival
PQst· 2020-03-17
35.6
best: 49.2 (OneFormer (InternImage-H,single-scale))
Axial-DeepLab: Stand-Alone Axial-Attention for Panoptic Segmentation arXiv:2003.07853
Panoptic SegmentationonCOCO minival
PQth· 2020-03-17
48.5
best: 67.1 (OneFormer (InternImage-H,single-scale))
Axial-DeepLab: Stand-Alone Axial-Attention for Panoptic Segmentation arXiv:2003.07853