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| Collections: | |
| - Name: MaskFormer | |
| License: Apache License 2.0 | |
| Metadata: | |
| Training Data: | |
| - Usage | |
| - ADE20K | |
| Paper: | |
| Title: 'MaskFormer: Per-Pixel Classification is Not All You Need for Semantic | |
| Segmentation' | |
| URL: https://arxiv.org/abs/2107.06278 | |
| README: configs/maskformer/README.md | |
| Frameworks: | |
| - PyTorch | |
| Models: | |
| - Name: maskformer_r50-d32_8xb2-160k_ade20k-512x512 | |
| In Collection: MaskFormer | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: ADE20K | |
| Metrics: | |
| mIoU: 44.29 | |
| Config: configs/maskformer/maskformer_r50-d32_8xb2-160k_ade20k-512x512.py | |
| Metadata: | |
| Training Data: ADE20K | |
| Batch Size: 16 | |
| Architecture: | |
| - R-50-D32 | |
| - MaskFormer | |
| Training Resources: 8x 42.20 GPUS | |
| Memory (GB): 3.29 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/maskformer/maskformer_r50-d32_8xb2-160k_ade20k-512x512/maskformer_r50-d32_8xb2-160k_ade20k-512x512_20221030_182724-3a9cfe45.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/maskformer/maskformer_r50-d32_8xb2-160k_ade20k-512x512/maskformer_r50-d32_8xb2-160k_ade20k-512x512_20221030_182724.json | |
| Paper: | |
| Title: 'MaskFormer: Per-Pixel Classification is Not All You Need for Semantic | |
| Segmentation' | |
| URL: https://arxiv.org/abs/2107.06278 | |
| Code: https://github.com/open-mmlab/mmdetection/blob/dev-3.x/mmdet/models/dense_heads/maskformer_head.py#L21 | |
| Framework: PyTorch | |
| - Name: maskformer_r101-d32_8xb2-160k_ade20k-512x512 | |
| In Collection: MaskFormer | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: ADE20K | |
| Metrics: | |
| mIoU: 45.11 | |
| Config: configs/maskformer/maskformer_r101-d32_8xb2-160k_ade20k-512x512.py | |
| Metadata: | |
| Training Data: ADE20K | |
| Batch Size: 16 | |
| Architecture: | |
| - R-101-D32 | |
| - MaskFormer | |
| Training Resources: 8x 34.90 GPUS | |
| Memory (GB): 4.12 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/maskformer/maskformer_r101-d32_8xb2-160k_ade20k-512x512/maskformer_r101-d32_8xb2-160k_ade20k-512x512_20221031_223053-84adbfcb.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/maskformer/maskformer_r101-d32_8xb2-160k_ade20k-512x512/maskformer_r101-d32_8xb2-160k_ade20k-512x512_20221031_223053.json | |
| Paper: | |
| Title: 'MaskFormer: Per-Pixel Classification is Not All You Need for Semantic | |
| Segmentation' | |
| URL: https://arxiv.org/abs/2107.06278 | |
| Code: https://github.com/open-mmlab/mmdetection/blob/dev-3.x/mmdet/models/dense_heads/maskformer_head.py#L21 | |
| Framework: PyTorch | |
| - Name: maskformer_swin-t_upernet_8xb2-160k_ade20k-512x512 | |
| In Collection: MaskFormer | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: ADE20K | |
| Metrics: | |
| mIoU: 46.69 | |
| Config: configs/maskformer/maskformer_swin-t_upernet_8xb2-160k_ade20k-512x512.py | |
| Metadata: | |
| Training Data: ADE20K | |
| Batch Size: 16 | |
| Architecture: | |
| - Swin-T | |
| - MaskFormer | |
| Training Resources: 8x 40.53 GPUS | |
| Memory (GB): 3.73 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/maskformer/maskformer_swin-t_upernet_8xb2-160k_ade20k-512x512/maskformer_swin-t_upernet_8xb2-160k_ade20k-512x512_20221114_232813-f14e7ce0.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/maskformer/maskformer_swin-t_upernet_8xb2-160k_ade20k-512x512/maskformer_swin-t_upernet_8xb2-160k_ade20k-512x512_20221114_232813.json | |
| Paper: | |
| Title: 'MaskFormer: Per-Pixel Classification is Not All You Need for Semantic | |
| Segmentation' | |
| URL: https://arxiv.org/abs/2107.06278 | |
| Code: https://github.com/open-mmlab/mmdetection/blob/dev-3.x/mmdet/models/dense_heads/maskformer_head.py#L21 | |
| Framework: PyTorch | |
| - Name: maskformer_swin-s_upernet_8xb2-160k_ade20k-512x512 | |
| In Collection: MaskFormer | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: ADE20K | |
| Metrics: | |
| mIoU: 49.36 | |
| Config: configs/maskformer/maskformer_swin-s_upernet_8xb2-160k_ade20k-512x512.py | |
| Metadata: | |
| Training Data: ADE20K | |
| Batch Size: 16 | |
| Architecture: | |
| - Swin-S | |
| - MaskFormer | |
| Training Resources: 8x 26.98 GPUS | |
| Memory (GB): 5.33 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/maskformer/maskformer_swin-s_upernet_8xb2-160k_ade20k-512x512/maskformer_swin-s_upernet_8xb2-160k_ade20k-512x512_20221115_114710-723512c7.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/maskformer/maskformer_swin-s_upernet_8xb2-160k_ade20k-512x512/maskformer_swin-s_upernet_8xb2-160k_ade20k-512x512_20221115_114710.json | |
| Paper: | |
| Title: 'MaskFormer: Per-Pixel Classification is Not All You Need for Semantic | |
| Segmentation' | |
| URL: https://arxiv.org/abs/2107.06278 | |
| Code: https://github.com/open-mmlab/mmdetection/blob/dev-3.x/mmdet/models/dense_heads/maskformer_head.py#L21 | |
| Framework: PyTorch | |