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483 lines
12 KiB
483 lines
12 KiB
# Deep Layer Aggregation
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Extending “shallow” skip connections, **Dense Layer Aggregation (DLA)** incorporates more depth and sharing. The authors introduce two structures for deep layer aggregation (DLA): iterative deep aggregation (IDA) and hierarchical deep aggregation (HDA). These structures are expressed through an architectural framework, independent of the choice of backbone, for compatibility with current and future networks.
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IDA focuses on fusing resolutions and scales while HDA focuses on merging features from all modules and channels. IDA follows the base hierarchy to refine resolution and aggregate scale stage-bystage. HDA assembles its own hierarchy of tree-structured connections that cross and merge stages to aggregate different levels of representation.
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{% include 'code_snippets.md' %}
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## How do I train this model?
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You can follow the [timm recipe scripts](https://rwightman.github.io/pytorch-image-models/scripts/) for training a new model afresh.
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## Citation
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```BibTeX
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@misc{yu2019deep,
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title={Deep Layer Aggregation},
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author={Fisher Yu and Dequan Wang and Evan Shelhamer and Trevor Darrell},
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year={2019},
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eprint={1707.06484},
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archivePrefix={arXiv},
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primaryClass={cs.CV}
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}
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```
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<!--
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Models:
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- Name: dla60
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Metadata:
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FLOPs: 4256251880
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Epochs: 120
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Batch Size: 256
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Training Data:
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- ImageNet
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Training Techniques:
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- SGD with Momentum
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- Weight Decay
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Training Resources: ''
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Architecture:
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- 1x1 Convolution
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- Batch Normalization
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- Convolution
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- DLA Bottleneck Residual Block
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- DLA Residual Block
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- Global Average Pooling
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- Max Pooling
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- ReLU
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- Residual Block
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- Residual Connection
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- Softmax
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File Size: 89560235
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Tasks:
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- Image Classification
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Training Time: ''
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ID: dla60
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LR: 0.1
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Layers: 60
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Dropout: 0.2
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Crop Pct: '0.875'
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Momentum: 0.9
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Image Size: '224'
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Weight Decay: 0.0001
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Interpolation: bilinear
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Code: https://github.com/rwightman/pytorch-image-models/blob/d8e69206be253892b2956341fea09fdebfaae4e3/timm/models/dla.py#L394
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Config: ''
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In Collection: DLA
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- Name: dla46_c
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Metadata:
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FLOPs: 583277288
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Epochs: 120
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Batch Size: 256
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Training Data:
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- ImageNet
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Training Techniques:
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- SGD with Momentum
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- Weight Decay
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Training Resources: ''
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Architecture:
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- 1x1 Convolution
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- Batch Normalization
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- Convolution
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- DLA Bottleneck Residual Block
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- DLA Residual Block
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- Global Average Pooling
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- Max Pooling
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- ReLU
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- Residual Block
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- Residual Connection
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- Softmax
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File Size: 5307963
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Tasks:
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- Image Classification
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Training Time: ''
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ID: dla46_c
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LR: 0.1
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Layers: 46
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Crop Pct: '0.875'
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Momentum: 0.9
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Image Size: '224'
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Weight Decay: 0.0001
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Interpolation: bilinear
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Code: https://github.com/rwightman/pytorch-image-models/blob/d8e69206be253892b2956341fea09fdebfaae4e3/timm/models/dla.py#L369
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Config: ''
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In Collection: DLA
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- Name: dla102x2
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Metadata:
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FLOPs: 9343847400
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Epochs: 120
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Batch Size: 256
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Training Data:
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- ImageNet
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Training Techniques:
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- SGD with Momentum
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- Weight Decay
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Training Resources: 8x GPUs
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Architecture:
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- 1x1 Convolution
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- Batch Normalization
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- Convolution
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- DLA Bottleneck Residual Block
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- DLA Residual Block
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- Global Average Pooling
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- Max Pooling
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- ReLU
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- Residual Block
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- Residual Connection
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- Softmax
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File Size: 167645295
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Tasks:
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- Image Classification
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Training Time: ''
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ID: dla102x2
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LR: 0.1
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Layers: 102
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Crop Pct: '0.875'
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Momentum: 0.9
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Image Size: '224'
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Weight Decay: 0.0001
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Interpolation: bilinear
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Code: https://github.com/rwightman/pytorch-image-models/blob/d8e69206be253892b2956341fea09fdebfaae4e3/timm/models/dla.py#L426
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Config: ''
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In Collection: DLA
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- Name: dla102
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Metadata:
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FLOPs: 7192952808
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Epochs: 120
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Batch Size: 256
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Training Data:
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- ImageNet
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Training Techniques:
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- SGD with Momentum
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- Weight Decay
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Training Resources: 8x GPUs
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Architecture:
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- 1x1 Convolution
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- Batch Normalization
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- Convolution
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- DLA Bottleneck Residual Block
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- DLA Residual Block
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- Global Average Pooling
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- Max Pooling
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- ReLU
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- Residual Block
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- Residual Connection
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- Softmax
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File Size: 135290579
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Tasks:
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- Image Classification
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Training Time: ''
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ID: dla102
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LR: 0.1
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Layers: 102
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Crop Pct: '0.875'
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Momentum: 0.9
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Image Size: '224'
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Weight Decay: 0.0001
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Interpolation: bilinear
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Code: https://github.com/rwightman/pytorch-image-models/blob/d8e69206be253892b2956341fea09fdebfaae4e3/timm/models/dla.py#L410
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Config: ''
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In Collection: DLA
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- Name: dla102x
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Metadata:
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FLOPs: 5886821352
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Epochs: 120
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Batch Size: 256
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Training Data:
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- ImageNet
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Training Techniques:
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- SGD with Momentum
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- Weight Decay
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Training Resources: 8x GPUs
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Architecture:
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- 1x1 Convolution
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- Batch Normalization
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- Convolution
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- DLA Bottleneck Residual Block
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- DLA Residual Block
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- Global Average Pooling
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- Max Pooling
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- ReLU
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- Residual Block
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- Residual Connection
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- Softmax
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File Size: 107552695
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Tasks:
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- Image Classification
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Training Time: ''
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ID: dla102x
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LR: 0.1
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Layers: 102
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Crop Pct: '0.875'
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Momentum: 0.9
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Image Size: '224'
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Weight Decay: 0.0001
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Interpolation: bilinear
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Code: https://github.com/rwightman/pytorch-image-models/blob/d8e69206be253892b2956341fea09fdebfaae4e3/timm/models/dla.py#L418
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Config: ''
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In Collection: DLA
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- Name: dla169
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Metadata:
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FLOPs: 11598004200
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Epochs: 120
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Batch Size: 256
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Training Data:
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- ImageNet
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Training Techniques:
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- SGD with Momentum
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- Weight Decay
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Training Resources: 8x GPUs
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Architecture:
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- 1x1 Convolution
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- Batch Normalization
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- Convolution
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- DLA Bottleneck Residual Block
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- DLA Residual Block
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- Global Average Pooling
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- Max Pooling
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- ReLU
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- Residual Block
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- Residual Connection
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- Softmax
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File Size: 216547113
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Tasks:
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- Image Classification
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Training Time: ''
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ID: dla169
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LR: 0.1
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Layers: 169
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Crop Pct: '0.875'
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Momentum: 0.9
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Image Size: '224'
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Weight Decay: 0.0001
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Interpolation: bilinear
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Code: https://github.com/rwightman/pytorch-image-models/blob/d8e69206be253892b2956341fea09fdebfaae4e3/timm/models/dla.py#L434
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Config: ''
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In Collection: DLA
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- Name: dla46x_c
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Metadata:
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FLOPs: 544052200
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Epochs: 120
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Batch Size: 256
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Training Data:
|
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- ImageNet
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Training Techniques:
|
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- SGD with Momentum
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- Weight Decay
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Training Resources: ''
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Architecture:
|
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- 1x1 Convolution
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- Batch Normalization
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- Convolution
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- DLA Bottleneck Residual Block
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- DLA Residual Block
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- Global Average Pooling
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- Max Pooling
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- ReLU
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- Residual Block
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- Residual Connection
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- Softmax
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File Size: 4387641
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Tasks:
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- Image Classification
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Training Time: ''
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ID: dla46x_c
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LR: 0.1
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Layers: 46
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Crop Pct: '0.875'
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Momentum: 0.9
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Image Size: '224'
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Weight Decay: 0.0001
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Interpolation: bilinear
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Code: https://github.com/rwightman/pytorch-image-models/blob/d8e69206be253892b2956341fea09fdebfaae4e3/timm/models/dla.py#L378
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Config: ''
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In Collection: DLA
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- Name: dla60_res2net
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Metadata:
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FLOPs: 4147578504
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Training Data:
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- ImageNet
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Training Techniques:
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- SGD with Momentum
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- Weight Decay
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Training Resources: ''
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Architecture:
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- 1x1 Convolution
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- Batch Normalization
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- Convolution
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- DLA Bottleneck Residual Block
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- DLA Residual Block
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- Global Average Pooling
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- Max Pooling
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- ReLU
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- Residual Block
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- Residual Connection
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- Softmax
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File Size: 84886593
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Tasks:
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- Image Classification
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Training Time: ''
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ID: dla60_res2net
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Layers: 60
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Crop Pct: '0.875'
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Image Size: '224'
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Interpolation: bilinear
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Code: https://github.com/rwightman/pytorch-image-models/blob/d8e69206be253892b2956341fea09fdebfaae4e3/timm/models/dla.py#L346
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Config: ''
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In Collection: DLA
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- Name: dla60_res2next
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Metadata:
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FLOPs: 3485335272
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Training Data:
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- ImageNet
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Training Techniques:
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- SGD with Momentum
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- Weight Decay
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Training Resources: ''
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Architecture:
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- 1x1 Convolution
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- Batch Normalization
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- Convolution
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- DLA Bottleneck Residual Block
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- DLA Residual Block
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- Global Average Pooling
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- Max Pooling
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- ReLU
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- Residual Block
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- Residual Connection
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- Softmax
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File Size: 69639245
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Tasks:
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- Image Classification
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Training Time: ''
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ID: dla60_res2next
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Layers: 60
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Crop Pct: '0.875'
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Image Size: '224'
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Interpolation: bilinear
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Code: https://github.com/rwightman/pytorch-image-models/blob/d8e69206be253892b2956341fea09fdebfaae4e3/timm/models/dla.py#L354
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Config: ''
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In Collection: DLA
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- Name: dla34
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Metadata:
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FLOPs: 3070105576
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Epochs: 120
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Batch Size: 256
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Training Data:
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- ImageNet
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Training Techniques:
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- SGD with Momentum
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- Weight Decay
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Training Resources: ''
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Architecture:
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- 1x1 Convolution
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- Batch Normalization
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- Convolution
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- DLA Bottleneck Residual Block
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- DLA Residual Block
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- Global Average Pooling
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- Max Pooling
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- ReLU
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- Residual Block
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- Residual Connection
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- Softmax
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File Size: 63228658
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Tasks:
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- Image Classification
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Training Time: ''
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ID: dla34
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LR: 0.1
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Layers: 32
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Crop Pct: '0.875'
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Momentum: 0.9
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Image Size: '224'
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Weight Decay: 0.0001
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Interpolation: bilinear
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Code: https://github.com/rwightman/pytorch-image-models/blob/d8e69206be253892b2956341fea09fdebfaae4e3/timm/models/dla.py#L362
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Config: ''
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In Collection: DLA
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- Name: dla60x
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Metadata:
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FLOPs: 3544204264
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Epochs: 120
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|
Batch Size: 256
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Training Data:
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- ImageNet
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|
Training Techniques:
|
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- SGD with Momentum
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- Weight Decay
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Training Resources: ''
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Architecture:
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- 1x1 Convolution
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- Batch Normalization
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- Convolution
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- DLA Bottleneck Residual Block
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- DLA Residual Block
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- Global Average Pooling
|
|
- Max Pooling
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- ReLU
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- Residual Block
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- Residual Connection
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- Softmax
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File Size: 70883139
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Tasks:
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- Image Classification
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Training Time: ''
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ID: dla60x
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LR: 0.1
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Layers: 60
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Crop Pct: '0.875'
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Momentum: 0.9
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Image Size: '224'
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Weight Decay: 0.0001
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Interpolation: bilinear
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Code: https://github.com/rwightman/pytorch-image-models/blob/d8e69206be253892b2956341fea09fdebfaae4e3/timm/models/dla.py#L402
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Config: ''
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In Collection: DLA
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- Name: dla60x_c
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|
Metadata:
|
|
FLOPs: 593325032
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|
Epochs: 120
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|
Batch Size: 256
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|
Training Data:
|
|
- ImageNet
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|
Training Techniques:
|
|
- SGD with Momentum
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|
- Weight Decay
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|
Training Resources: ''
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|
Architecture:
|
|
- 1x1 Convolution
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|
- Batch Normalization
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|
- Convolution
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|
- DLA Bottleneck Residual Block
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|
- DLA Residual Block
|
|
- Global Average Pooling
|
|
- Max Pooling
|
|
- ReLU
|
|
- Residual Block
|
|
- Residual Connection
|
|
- Softmax
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|
File Size: 5454396
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|
Tasks:
|
|
- Image Classification
|
|
Training Time: ''
|
|
ID: dla60x_c
|
|
LR: 0.1
|
|
Layers: 60
|
|
Crop Pct: '0.875'
|
|
Momentum: 0.9
|
|
Image Size: '224'
|
|
Weight Decay: 0.0001
|
|
Interpolation: bilinear
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|
Code: https://github.com/rwightman/pytorch-image-models/blob/d8e69206be253892b2956341fea09fdebfaae4e3/timm/models/dla.py#L386
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Config: ''
|
|
In Collection: DLA
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Collections:
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- Name: DLA
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Paper:
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title: Deep Layer Aggregation
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url: https://paperswithcode.com//paper/deep-layer-aggregation
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type: model-index
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Type: model-index
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|
-->
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