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153 lines
4.2 KiB
153 lines
4.2 KiB
3 years ago
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# ResNeXt
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3 years ago
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A **ResNeXt** repeats a [building block](https://paperswithcode.com/method/resnext-block) that aggregates a set of transformations with the same topology. Compared to a [ResNet](https://paperswithcode.com/method/resnet), it exposes a new dimension, *cardinality* (the size of the set of transformations) $C$, as an essential factor in addition to the dimensions of depth and width.
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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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@article{DBLP:journals/corr/XieGDTH16,
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author = {Saining Xie and
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Ross B. Girshick and
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Piotr Doll{\'{a}}r and
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Zhuowen Tu and
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Kaiming He},
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title = {Aggregated Residual Transformations for Deep Neural Networks},
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journal = {CoRR},
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volume = {abs/1611.05431},
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year = {2016},
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url = {http://arxiv.org/abs/1611.05431},
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archivePrefix = {arXiv},
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eprint = {1611.05431},
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timestamp = {Mon, 13 Aug 2018 16:45:58 +0200},
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biburl = {https://dblp.org/rec/journals/corr/XieGDTH16.bib},
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bibsource = {dblp computer science bibliography, https://dblp.org}
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}
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```
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<!--
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Models:
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- Name: resnext101_32x8d
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Metadata:
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FLOPs: 21180417024
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Training Data:
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- ImageNet
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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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- Global Average Pooling
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- Grouped Convolution
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- Max Pooling
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- ReLU
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- ResNeXt Block
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- Residual Connection
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- Softmax
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File Size: 356082095
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Tasks:
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- Image Classification
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ID: resnext101_32x8d
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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/b9843f954b0457af2db4f9dea41a8538f51f5d78/timm/models/resnet.py#L877
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In Collection: ResNeXt
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- Name: resnext50_32x4d
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Metadata:
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FLOPs: 5472648192
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Training Data:
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- ImageNet
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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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- Global Average Pooling
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- Grouped Convolution
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- Max Pooling
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- ReLU
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- ResNeXt Block
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- Residual Connection
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- Softmax
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File Size: 100435887
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Tasks:
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- Image Classification
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ID: resnext50_32x4d
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Crop Pct: '0.875'
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Image Size: '224'
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Interpolation: bicubic
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Code: https://github.com/rwightman/pytorch-image-models/blob/b9843f954b0457af2db4f9dea41a8538f51f5d78/timm/models/resnet.py#L851
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In Collection: ResNeXt
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- Name: tv_resnext50_32x4d
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Metadata:
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FLOPs: 5472648192
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Epochs: 90
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Batch Size: 32
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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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Architecture:
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- 1x1 Convolution
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- Batch Normalization
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- Convolution
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- Global Average Pooling
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- Grouped Convolution
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- Max Pooling
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- ReLU
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- ResNeXt Block
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- Residual Connection
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- Softmax
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File Size: 100441675
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Tasks:
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- Image Classification
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ID: tv_resnext50_32x4d
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LR: 0.1
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Crop Pct: '0.875'
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LR Gamma: 0.1
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Momentum: 0.9
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Image Size: '224'
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LR Step Size: 30
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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/9a25fdf3ad0414b4d66da443fe60ae0aa14edc84/timm/models/resnet.py#L842
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In Collection: ResNeXt
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- Name: resnext50d_32x4d
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Metadata:
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FLOPs: 5781119488
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Training Data:
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- ImageNet
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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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- Global Average Pooling
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- Grouped Convolution
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- Max Pooling
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- ReLU
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- ResNeXt Block
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- Residual Connection
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- Softmax
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File Size: 100515304
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Tasks:
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- Image Classification
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ID: resnext50d_32x4d
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Crop Pct: '0.875'
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Image Size: '224'
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Interpolation: bicubic
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Code: https://github.com/rwightman/pytorch-image-models/blob/b9843f954b0457af2db4f9dea41a8538f51f5d78/timm/models/resnet.py#L869
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In Collection: ResNeXt
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Collections:
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- Name: ResNeXt
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Paper:
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title: Aggregated Residual Transformations for Deep Neural Networks
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3 years ago
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url: https://paperswithcode.com//paper/aggregated-residual-transformations-for-deep
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3 years ago
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type: model-index
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Type: model-index
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-->
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