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| Collections: | |
| - Name: KNet | |
| License: Apache License 2.0 | |
| Metadata: | |
| Training Data: | |
| - ADE20K | |
| Paper: | |
| Title: 'K-Net: Towards Unified Image Segmentation' | |
| URL: https://arxiv.org/abs/2106.14855 | |
| README: configs/knet/README.md | |
| Frameworks: | |
| - PyTorch | |
| Models: | |
| - Name: knet-s3_r50-d8_fcn_8xb2-adamw-80k_ade20k-512x512 | |
| In Collection: KNet | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: ADE20K | |
| Metrics: | |
| mIoU: 43.6 | |
| mIoU(ms+flip): 45.12 | |
| Config: configs/knet/knet-s3_r50-d8_fcn_8xb2-adamw-80k_ade20k-512x512.py | |
| Metadata: | |
| Training Data: ADE20K | |
| Batch Size: 16 | |
| Architecture: | |
| - R-50-D8 | |
| - KNet | |
| - FCN | |
| Training Resources: 8x V100 GPUS | |
| Memory (GB): 7.01 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/knet/knet_s3_fcn_r50-d8_8x2_512x512_adamw_80k_ade20k/knet_s3_fcn_r50-d8_8x2_512x512_adamw_80k_ade20k_20220228_043751-abcab920.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/knet/knet_s3_fcn_r50-d8_8x2_512x512_adamw_80k_ade20k/knet_s3_fcn_r50-d8_8x2_512x512_adamw_80k_ade20k_20220228_043751.log.json | |
| Paper: | |
| Title: 'K-Net: Towards Unified Image Segmentation' | |
| URL: https://arxiv.org/abs/2106.14855 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.23.0/mmseg/models/decode_heads/knet_head.py#L392 | |
| Framework: PyTorch | |
| - Name: knet-s3_r50-d8_pspnet_8xb2-adamw-80k_ade20k-512x512 | |
| In Collection: KNet | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: ADE20K | |
| Metrics: | |
| mIoU: 44.18 | |
| mIoU(ms+flip): 45.58 | |
| Config: configs/knet/knet-s3_r50-d8_pspnet_8xb2-adamw-80k_ade20k-512x512.py | |
| Metadata: | |
| Training Data: ADE20K | |
| Batch Size: 16 | |
| Architecture: | |
| - R-50-D8 | |
| - KNet | |
| - PSPNet | |
| Training Resources: 8x V100 GPUS | |
| Memory (GB): 6.98 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/knet/knet_s3_pspnet_r50-d8_8x2_512x512_adamw_80k_ade20k/knet_s3_pspnet_r50-d8_8x2_512x512_adamw_80k_ade20k_20220228_054634-d2c72240.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/knet/knet_s3_pspnet_r50-d8_8x2_512x512_adamw_80k_ade20k/knet_s3_pspnet_r50-d8_8x2_512x512_adamw_80k_ade20k_20220228_054634.log.json | |
| Paper: | |
| Title: 'K-Net: Towards Unified Image Segmentation' | |
| URL: https://arxiv.org/abs/2106.14855 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.23.0/mmseg/models/decode_heads/knet_head.py#L392 | |
| Framework: PyTorch | |
| - Name: knet-s3_r50-d8_deeplabv3_8xb2-adamw-80k_ade20k-512x512 | |
| In Collection: KNet | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: ADE20K | |
| Metrics: | |
| mIoU: 45.06 | |
| mIoU(ms+flip): 46.11 | |
| Config: configs/knet/knet-s3_r50-d8_deeplabv3_8xb2-adamw-80k_ade20k-512x512.py | |
| Metadata: | |
| Training Data: ADE20K | |
| Batch Size: 16 | |
| Architecture: | |
| - R-50-D8 | |
| - KNet | |
| - DeepLabV3 | |
| Training Resources: 8x V100 GPUS | |
| Memory (GB): 7.42 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/knet/knet_s3_deeplabv3_r50-d8_8x2_512x512_adamw_80k_ade20k/knet_s3_deeplabv3_r50-d8_8x2_512x512_adamw_80k_ade20k_20220228_041642-00c8fbeb.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/knet/knet_s3_deeplabv3_r50-d8_8x2_512x512_adamw_80k_ade20k/knet_s3_deeplabv3_r50-d8_8x2_512x512_adamw_80k_ade20k_20220228_041642.log.json | |
| Paper: | |
| Title: 'K-Net: Towards Unified Image Segmentation' | |
| URL: https://arxiv.org/abs/2106.14855 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.23.0/mmseg/models/decode_heads/knet_head.py#L392 | |
| Framework: PyTorch | |
| - Name: knet-s3_r50-d8_upernet_8xb2-adamw-80k_ade20k-512x512 | |
| In Collection: KNet | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: ADE20K | |
| Metrics: | |
| mIoU: 43.45 | |
| mIoU(ms+flip): 44.07 | |
| Config: configs/knet/knet-s3_r50-d8_upernet_8xb2-adamw-80k_ade20k-512x512.py | |
| Metadata: | |
| Training Data: ADE20K | |
| Batch Size: 16 | |
| Architecture: | |
| - R-50-D8 | |
| - KNet | |
| - UperNet | |
| Training Resources: 8x V100 GPUS | |
| Memory (GB): 7.34 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/knet/knet_s3_upernet_r50-d8_8x2_512x512_adamw_80k_ade20k/knet_s3_upernet_r50-d8_8x2_512x512_adamw_80k_ade20k_20220304_125657-215753b0.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/knet/knet_s3_upernet_r50-d8_8x2_512x512_adamw_80k_ade20k/knet_s3_upernet_r50-d8_8x2_512x512_adamw_80k_ade20k_20220304_125657.log.json | |
| Paper: | |
| Title: 'K-Net: Towards Unified Image Segmentation' | |
| URL: https://arxiv.org/abs/2106.14855 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.23.0/mmseg/models/decode_heads/knet_head.py#L392 | |
| Framework: PyTorch | |
| - Name: knet-s3_swin-t_upernet_8xb2-adamw-80k_ade20k-512x512 | |
| In Collection: KNet | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: ADE20K | |
| Metrics: | |
| mIoU: 45.84 | |
| mIoU(ms+flip): 46.27 | |
| Config: configs/knet/knet-s3_swin-t_upernet_8xb2-adamw-80k_ade20k-512x512.py | |
| Metadata: | |
| Training Data: ADE20K | |
| Batch Size: 16 | |
| Architecture: | |
| - Swin-T | |
| - KNet | |
| - UperNet | |
| Training Resources: 8x V100 GPUS | |
| Memory (GB): 7.57 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/knet/knet_s3_upernet_swin-t_8x2_512x512_adamw_80k_ade20k/knet_s3_upernet_swin-t_8x2_512x512_adamw_80k_ade20k_20220303_133059-7545e1dc.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/knet/knet_s3_upernet_swin-t_8x2_512x512_adamw_80k_ade20k/knet_s3_upernet_swin-t_8x2_512x512_adamw_80k_ade20k_20220303_133059.log.json | |
| Paper: | |
| Title: 'K-Net: Towards Unified Image Segmentation' | |
| URL: https://arxiv.org/abs/2106.14855 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.23.0/mmseg/models/decode_heads/knet_head.py#L392 | |
| Framework: PyTorch | |
| - Name: knet-s3_swin-l_upernet_8xb2-adamw-80k_ade20k-512x512 | |
| In Collection: KNet | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: ADE20K | |
| Metrics: | |
| mIoU: 52.05 | |
| mIoU(ms+flip): 53.24 | |
| Config: configs/knet/knet-s3_swin-l_upernet_8xb2-adamw-80k_ade20k-512x512.py | |
| Metadata: | |
| Training Data: ADE20K | |
| Batch Size: 16 | |
| Architecture: | |
| - Swin-L | |
| - KNet | |
| - UperNet | |
| Training Resources: 8x V100 GPUS | |
| Memory (GB): 13.5 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/knet/knet_s3_upernet_swin-l_8x2_512x512_adamw_80k_ade20k/knet_s3_upernet_swin-l_8x2_512x512_adamw_80k_ade20k_20220303_154559-d8da9a90.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/knet/knet_s3_upernet_swin-l_8x2_512x512_adamw_80k_ade20k/knet_s3_upernet_swin-l_8x2_512x512_adamw_80k_ade20k_20220303_154559.log.json | |
| Paper: | |
| Title: 'K-Net: Towards Unified Image Segmentation' | |
| URL: https://arxiv.org/abs/2106.14855 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.23.0/mmseg/models/decode_heads/knet_head.py#L392 | |
| Framework: PyTorch | |
| - Name: knet-s3_swin-l_upernet_8xb2-adamw-80k_ade20k-640x640 | |
| In Collection: KNet | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: ADE20K | |
| Metrics: | |
| mIoU: 52.21 | |
| mIoU(ms+flip): 53.34 | |
| Config: configs/knet/knet-s3_swin-l_upernet_8xb2-adamw-80k_ade20k-640x640.py | |
| Metadata: | |
| Training Data: ADE20K | |
| Batch Size: 16 | |
| Architecture: | |
| - Swin-L | |
| - KNet | |
| - UperNet | |
| Training Resources: 8x V100 GPUS | |
| Memory (GB): 13.54 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/knet/knet_s3_upernet_swin-l_8x2_640x640_adamw_80k_ade20k/knet_s3_upernet_swin-l_8x2_640x640_adamw_80k_ade20k_20220301_220747-8787fc71.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/knet/knet_s3_upernet_swin-l_8x2_640x640_adamw_80k_ade20k/knet_s3_upernet_swin-l_8x2_640x640_adamw_80k_ade20k_20220301_220747.log.json | |
| Paper: | |
| Title: 'K-Net: Towards Unified Image Segmentation' | |
| URL: https://arxiv.org/abs/2106.14855 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.23.0/mmseg/models/decode_heads/knet_head.py#L392 | |
| Framework: PyTorch | |