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Models/Mask2Former (Swin-T)

Mask2Former (Swin-T)

Reported on 9 benchmarks across 4 tasks · 3 papers · 5 SOTA

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

Medical3 results

Semantic SegmentationonMUSES: MUlti-SEnsor Semantic perception dataset
mIoU· 2024-01-23
70.74
best: 78.2 (CAFuser (Swin-T))
SOTA
MUSES: The Multi-Sensor Semantic Perception Dataset for Driving under Uncertainty arXiv:2401.12761
Semantic SegmentationonMUSES: MUlti-SEnsor Semantic perception dataset
AUPQ· 2024-01-23
44.3
SOTA
MUSES: The Multi-Sensor Semantic Perception Dataset for Driving under Uncertainty arXiv:2401.12761
Semantic SegmentationonLaRS
PQ· 2023-08-18
39.2
best: 41.7 (Mask2Former (Swin-B))
LaRS: A Diverse Panoptic Maritime Obstacle Detection Dataset and Benchmark arXiv:2308.09618

Audio3 results

10-shot image generationonMUSES: MUlti-SEnsor Semantic perception dataset
mIoU· 2024-01-23
70.74
best: 78.2 (CAFuser (Swin-T))
SOTA
MUSES: The Multi-Sensor Semantic Perception Dataset for Driving under Uncertainty arXiv:2401.12761
10-shot image generationonMUSES: MUlti-SEnsor Semantic perception dataset
AUPQ· 2024-01-23
44.3
SOTA
MUSES: The Multi-Sensor Semantic Perception Dataset for Driving under Uncertainty arXiv:2401.12761
10-shot image generationonLaRS
PQ· 2023-08-18
39.2
best: 41.7 (Mask2Former (Swin-B))
LaRS: A Diverse Panoptic Maritime Obstacle Detection Dataset and Benchmark arXiv:2308.09618

Computer Vision3 results

Panoptic SegmentationonMUSES: MUlti-SEnsor Semantic perception dataset
AUPQ· 2024-01-23
44.3
SOTA
MUSES: The Multi-Sensor Semantic Perception Dataset for Driving under Uncertainty arXiv:2401.12761
Panoptic SegmentationonLaRS
PQ· 2023-08-18
39.2
best: 41.7 (Mask2Former (Swin-B))
LaRS: A Diverse Panoptic Maritime Obstacle Detection Dataset and Benchmark arXiv:2308.09618
Instance SegmentationonCityscapes val
mask AP· 2021-12-02
39.7
best: 49 (ViT-P (OneFormer, ConvNeXt-L, single-scale, 512x1024, Mapillary Vistas-pretrained))
Masked-attention Mask Transformer for Universal Image Segmentation arXiv:2112.01527