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| Collections: | |
| - Name: BiSeNetV1 | |
| License: Apache License 2.0 | |
| Metadata: | |
| Training Data: | |
| - Cityscapes | |
| - COCO-Stuff 164k | |
| Paper: | |
| Title: 'BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation' | |
| URL: https://arxiv.org/abs/1808.00897 | |
| README: configs/bisenetv1/README.md | |
| Frameworks: | |
| - PyTorch | |
| Models: | |
| - Name: bisenetv1_r18-d32_4xb4-160k_cityscapes-1024x1024 | |
| In Collection: BiSeNetV1 | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Cityscapes | |
| Metrics: | |
| mIoU: 74.44 | |
| mIoU(ms+flip): 77.05 | |
| Config: configs/bisenetv1/bisenetv1_r18-d32_4xb4-160k_cityscapes-1024x1024.py | |
| Metadata: | |
| Training Data: Cityscapes | |
| Batch Size: 16 | |
| Architecture: | |
| - R-18-D32 | |
| - BiSeNetV1 | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 5.69 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/bisenetv1/bisenetv1_r18-d32_4x4_1024x1024_160k_cityscapes/bisenetv1_r18-d32_4x4_1024x1024_160k_cityscapes_20210922_172239-c55e78e2.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/bisenetv1/bisenetv1_r18-d32_4x4_1024x1024_160k_cityscapes/bisenetv1_r18-d32_4x4_1024x1024_160k_cityscapes_20210922_172239.log.json | |
| Paper: | |
| Title: 'BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation' | |
| URL: https://arxiv.org/abs/1808.00897 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.18.0/mmseg/models/backbones/bisenetv1.py#L266 | |
| Framework: PyTorch | |
| - Name: bisenetv1_r18-d32-in1k-pre_4xb4-160k_cityscapes-1024x1024 | |
| In Collection: BiSeNetV1 | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Cityscapes | |
| Metrics: | |
| mIoU: 74.37 | |
| mIoU(ms+flip): 76.91 | |
| Config: configs/bisenetv1/bisenetv1_r18-d32-in1k-pre_4xb4-160k_cityscapes-1024x1024.py | |
| Metadata: | |
| Training Data: Cityscapes | |
| Batch Size: 16 | |
| Architecture: | |
| - R-18-D32 | |
| - BiSeNetV1 | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 5.69 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/bisenetv1/bisenetv1_r18-d32_in1k-pre_4x4_1024x1024_160k_cityscapes/bisenetv1_r18-d32_in1k-pre_4x4_1024x1024_160k_cityscapes_20210905_220251-8ba80eff.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/bisenetv1/bisenetv1_r18-d32_in1k-pre_4x4_1024x1024_160k_cityscapes/bisenetv1_r18-d32_in1k-pre_4x4_1024x1024_160k_cityscapes_20210905_220251.log.json | |
| Paper: | |
| Title: 'BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation' | |
| URL: https://arxiv.org/abs/1808.00897 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.18.0/mmseg/models/backbones/bisenetv1.py#L266 | |
| Framework: PyTorch | |
| - Name: bisenetv1_r18-d32-in1k-pre_4xb8-160k_cityscapes-1024x1024 | |
| In Collection: BiSeNetV1 | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Cityscapes | |
| Metrics: | |
| mIoU: 75.16 | |
| mIoU(ms+flip): 77.24 | |
| Config: configs/bisenetv1/bisenetv1_r18-d32-in1k-pre_4xb8-160k_cityscapes-1024x1024.py | |
| Metadata: | |
| Training Data: Cityscapes | |
| Batch Size: 32 | |
| Architecture: | |
| - R-18-D32 | |
| - BiSeNetV1 | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 11.17 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/bisenetv1/bisenetv1_r18-d32_in1k-pre_4x8_1024x1024_160k_cityscapes/bisenetv1_r18-d32_in1k-pre_4x8_1024x1024_160k_cityscapes_20210905_220322-bb8db75f.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/bisenetv1/bisenetv1_r18-d32_in1k-pre_4x8_1024x1024_160k_cityscapes/bisenetv1_r18-d32_in1k-pre_4x8_1024x1024_160k_cityscapes_20210905_220322.log.json | |
| Paper: | |
| Title: 'BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation' | |
| URL: https://arxiv.org/abs/1808.00897 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.18.0/mmseg/models/backbones/bisenetv1.py#L266 | |
| Framework: PyTorch | |
| - Name: bisenetv1_r50-d32_4xb4-160k_cityscapes-1024x1024 | |
| In Collection: BiSeNetV1 | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Cityscapes | |
| Metrics: | |
| mIoU: 76.92 | |
| mIoU(ms+flip): 78.87 | |
| Config: configs/bisenetv1/bisenetv1_r50-d32_4xb4-160k_cityscapes-1024x1024.py | |
| Metadata: | |
| Training Data: Cityscapes | |
| Batch Size: 16 | |
| Architecture: | |
| - R-50-D32 | |
| - BiSeNetV1 | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 15.39 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/bisenetv1/bisenetv1_r50-d32_4x4_1024x1024_160k_cityscapes/bisenetv1_r50-d32_4x4_1024x1024_160k_cityscapes_20210923_222639-7b28a2a6.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/bisenetv1/bisenetv1_r50-d32_4x4_1024x1024_160k_cityscapes/bisenetv1_r50-d32_4x4_1024x1024_160k_cityscapes_20210923_222639.log.json | |
| Paper: | |
| Title: 'BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation' | |
| URL: https://arxiv.org/abs/1808.00897 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.18.0/mmseg/models/backbones/bisenetv1.py#L266 | |
| Framework: PyTorch | |
| - Name: bisenetv1_r50-d32-in1k-pre_4xb4-160k_cityscapes-1024x1024 | |
| In Collection: BiSeNetV1 | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Cityscapes | |
| Metrics: | |
| mIoU: 77.68 | |
| mIoU(ms+flip): 79.57 | |
| Config: configs/bisenetv1/bisenetv1_r50-d32-in1k-pre_4xb4-160k_cityscapes-1024x1024.py | |
| Metadata: | |
| Training Data: Cityscapes | |
| Batch Size: 16 | |
| Architecture: | |
| - R-50-D32 | |
| - BiSeNetV1 | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 15.39 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/bisenetv1/bisenetv1_r50-d32_in1k-pre_4x4_1024x1024_160k_cityscapes/bisenetv1_r50-d32_in1k-pre_4x4_1024x1024_160k_cityscapes_20210917_234628-8b304447.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/bisenetv1/bisenetv1_r50-d32_in1k-pre_4x4_1024x1024_160k_cityscapes/bisenetv1_r50-d32_in1k-pre_4x4_1024x1024_160k_cityscapes_20210917_234628.log.json | |
| Paper: | |
| Title: 'BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation' | |
| URL: https://arxiv.org/abs/1808.00897 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.18.0/mmseg/models/backbones/bisenetv1.py#L266 | |
| Framework: PyTorch | |
| - Name: bisenetv1_r18-d32_4xb4-160k_coco-stuff164k-512x512 | |
| In Collection: BiSeNetV1 | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: COCO-Stuff 164k | |
| Metrics: | |
| mIoU: 25.45 | |
| mIoU(ms+flip): 26.15 | |
| Config: configs/bisenetv1/bisenetv1_r18-d32_4xb4-160k_coco-stuff164k-512x512.py | |
| Metadata: | |
| Training Data: COCO-Stuff 164k | |
| Batch Size: 16 | |
| Architecture: | |
| - R-18-D32 | |
| - BiSeNetV1 | |
| Training Resources: 4x V100 GPUS | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/bisenetv1/bisenetv1_r18-d32_lr5e-3_4x4_512x512_160k_coco-stuff164k/bisenetv1_r18-d32_lr5e-3_4x4_512x512_160k_coco-stuff164k_20211022_054328-046aa2f2.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/bisenetv1/bisenetv1_r18-d32_lr5e-3_4x4_512x512_160k_coco-stuff164k/bisenetv1_r18-d32_lr5e-3_4x4_512x512_160k_coco-stuff164k_20211022_054328.log.json | |
| Paper: | |
| Title: 'BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation' | |
| URL: https://arxiv.org/abs/1808.00897 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.18.0/mmseg/models/backbones/bisenetv1.py#L266 | |
| Framework: PyTorch | |
| - Name: bisenetv1_r18-d32-in1k-pre_4xb4-160k_coco-stuff164k-512x512 | |
| In Collection: BiSeNetV1 | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: COCO-Stuff 164k | |
| Metrics: | |
| mIoU: 28.55 | |
| mIoU(ms+flip): 29.26 | |
| Config: configs/bisenetv1/bisenetv1_r18-d32-in1k-pre_4xb4-160k_coco-stuff164k-512x512.py | |
| Metadata: | |
| Training Data: COCO-Stuff 164k | |
| Batch Size: 16 | |
| Architecture: | |
| - R-18-D32 | |
| - BiSeNetV1 | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 6.33 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/bisenetv1/bisenetv1_r18-d32_in1k-pre_lr5e-3_4x4_512x512_160k_coco-stuff164k/bisenetv1_r18-d32_in1k-pre_lr5e-3_4x4_512x512_160k_coco-stuff164k_20211023_013100-f700dbf7.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/bisenetv1/bisenetv1_r18-d32_in1k-pre_lr5e-3_4x4_512x512_160k_coco-stuff164k/bisenetv1_r18-d32_in1k-pre_lr5e-3_4x4_512x512_160k_coco-stuff164k_20211023_013100.log.json | |
| Paper: | |
| Title: 'BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation' | |
| URL: https://arxiv.org/abs/1808.00897 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.18.0/mmseg/models/backbones/bisenetv1.py#L266 | |
| Framework: PyTorch | |
| - Name: bisenetv1_r50-d32_4xb4-160k_coco-stuff164k-512x512 | |
| In Collection: BiSeNetV1 | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: COCO-Stuff 164k | |
| Metrics: | |
| mIoU: 29.82 | |
| mIoU(ms+flip): 30.33 | |
| Config: configs/bisenetv1/bisenetv1_r50-d32_4xb4-160k_coco-stuff164k-512x512.py | |
| Metadata: | |
| Training Data: COCO-Stuff 164k | |
| Batch Size: 16 | |
| Architecture: | |
| - R-50-D32 | |
| - BiSeNetV1 | |
| Training Resources: 4x V100 GPUS | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/bisenetv1/bisenetv1_r50-d32_lr5e-3_4x4_512x512_160k_coco-stuff164k/bisenetv1_r50-d32_lr5e-3_4x4_512x512_160k_coco-stuff164k_20211101_040616-d2bb0df4.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/bisenetv1/bisenetv1_r50-d32_lr5e-3_4x4_512x512_160k_coco-stuff164k/bisenetv1_r50-d32_lr5e-3_4x4_512x512_160k_coco-stuff164k_20211101_040616.log.json | |
| Paper: | |
| Title: 'BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation' | |
| URL: https://arxiv.org/abs/1808.00897 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.18.0/mmseg/models/backbones/bisenetv1.py#L266 | |
| Framework: PyTorch | |
| - Name: bisenetv1_r50-d32-in1k-pre_4xb4-160k_coco-stuff164k-512x512 | |
| In Collection: BiSeNetV1 | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: COCO-Stuff 164k | |
| Metrics: | |
| mIoU: 34.88 | |
| mIoU(ms+flip): 35.37 | |
| Config: configs/bisenetv1/bisenetv1_r50-d32-in1k-pre_4xb4-160k_coco-stuff164k-512x512.py | |
| Metadata: | |
| Training Data: COCO-Stuff 164k | |
| Batch Size: 16 | |
| Architecture: | |
| - R-50-D32 | |
| - BiSeNetV1 | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 9.28 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/bisenetv1/bisenetv1_r50-d32_in1k-pre_lr5e-3_4x4_512x512_160k_coco-stuff164k/bisenetv1_r50-d32_in1k-pre_lr5e-3_4x4_512x512_160k_coco-stuff164k_20211101_181932-66747911.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/bisenetv1/bisenetv1_r50-d32_in1k-pre_lr5e-3_4x4_512x512_160k_coco-stuff164k/bisenetv1_r50-d32_in1k-pre_lr5e-3_4x4_512x512_160k_coco-stuff164k_20211101_181932.log.json | |
| Paper: | |
| Title: 'BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation' | |
| URL: https://arxiv.org/abs/1808.00897 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.18.0/mmseg/models/backbones/bisenetv1.py#L266 | |
| Framework: PyTorch | |
| - Name: bisenetv1_r50-d32-in1k-pre_4xb4-160k_coco-stuff164k-512x512 | |
| In Collection: BiSeNetV1 | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: COCO-Stuff 164k | |
| Metrics: | |
| mIoU: 31.14 | |
| mIoU(ms+flip): 31.76 | |
| Config: configs/bisenetv1/bisenetv1_r50-d32-in1k-pre_4xb4-160k_coco-stuff164k-512x512.py | |
| Metadata: | |
| Training Data: COCO-Stuff 164k | |
| Batch Size: 16 | |
| Architecture: | |
| - R-101-D32 | |
| - BiSeNetV1 | |
| Training Resources: 4x V100 GPUS | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/bisenetv1/bisenetv1_r101-d32_lr5e-3_4x4_512x512_160k_coco-stuff164k/bisenetv1_r101-d32_lr5e-3_4x4_512x512_160k_coco-stuff164k_20211102_164147-c6b32c3b.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/bisenetv1/bisenetv1_r101-d32_lr5e-3_4x4_512x512_160k_coco-stuff164k/bisenetv1_r101-d32_lr5e-3_4x4_512x512_160k_coco-stuff164k_20211102_164147.log.json | |
| Paper: | |
| Title: 'BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation' | |
| URL: https://arxiv.org/abs/1808.00897 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.18.0/mmseg/models/backbones/bisenetv1.py#L266 | |
| Framework: PyTorch | |
| - Name: bisenetv1_r101-d32-in1k-pre_4xb4-160k_coco-stuff164k-512x512 | |
| In Collection: BiSeNetV1 | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: COCO-Stuff 164k | |
| Metrics: | |
| mIoU: 37.38 | |
| mIoU(ms+flip): 37.99 | |
| Config: configs/bisenetv1/bisenetv1_r101-d32-in1k-pre_4xb4-160k_coco-stuff164k-512x512.py | |
| Metadata: | |
| Training Data: COCO-Stuff 164k | |
| Batch Size: 16 | |
| Architecture: | |
| - R-101-D32 | |
| - BiSeNetV1 | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 10.36 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/bisenetv1/bisenetv1_r101-d32_in1k-pre_lr5e-3_4x4_512x512_160k_coco-stuff164k/bisenetv1_r101-d32_in1k-pre_lr5e-3_4x4_512x512_160k_coco-stuff164k_20211101_225220-28c8f092.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/bisenetv1/bisenetv1_r101-d32_in1k-pre_lr5e-3_4x4_512x512_160k_coco-stuff164k/bisenetv1_r101-d32_in1k-pre_lr5e-3_4x4_512x512_160k_coco-stuff164k_20211101_225220.log.json | |
| Paper: | |
| Title: 'BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation' | |
| URL: https://arxiv.org/abs/1808.00897 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.18.0/mmseg/models/backbones/bisenetv1.py#L266 | |
| Framework: PyTorch | |