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137 lines
3.8 KiB
137 lines
3.8 KiB
# SelecSLS
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**SelecSLS** uses novel selective long and short range skip connections to improve the information flow allowing for a drastically faster network without compromising accuracy.
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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{Mehta_2020,
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title={XNect},
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volume={39},
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ISSN={1557-7368},
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url={http://dx.doi.org/10.1145/3386569.3392410},
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DOI={10.1145/3386569.3392410},
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number={4},
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journal={ACM Transactions on Graphics},
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publisher={Association for Computing Machinery (ACM)},
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author={Mehta, Dushyant and Sotnychenko, Oleksandr and Mueller, Franziska and Xu, Weipeng and Elgharib, Mohamed and Fua, Pascal and Seidel, Hans-Peter and Rhodin, Helge and Pons-Moll, Gerard and Theobalt, Christian},
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year={2020},
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month={Jul}
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}
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```
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<!--
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Type: model-index
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Collections:
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- Name: SelecSLS
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Paper:
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Title: 'XNect: Real-time Multi-Person 3D Motion Capture with a Single RGB Camera'
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URL: https://paperswithcode.com/paper/xnect-real-time-multi-person-3d-human-pose
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Models:
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- Name: selecsls42b
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In Collection: SelecSLS
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Metadata:
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FLOPs: 3824022528
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Parameters: 32460000
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File Size: 129948954
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Architecture:
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- Batch Normalization
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- Convolution
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- Dense Connections
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- Dropout
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- Global Average Pooling
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- ReLU
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- SelecSLS Block
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Tasks:
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- Image Classification
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Training Techniques:
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- Cosine Annealing
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- Random Erasing
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Training Data:
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- ImageNet
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ID: selecsls42b
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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/selecsls.py#L335
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Weights: https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-selecsls/selecsls42b-8af30141.pth
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Results:
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- Task: Image Classification
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Dataset: ImageNet
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Metrics:
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Top 1 Accuracy: 77.18%
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Top 5 Accuracy: 93.39%
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- Name: selecsls60
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In Collection: SelecSLS
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Metadata:
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FLOPs: 4610472600
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Parameters: 30670000
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File Size: 122839714
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Architecture:
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- Batch Normalization
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- Convolution
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- Dense Connections
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- Dropout
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- Global Average Pooling
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- ReLU
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- SelecSLS Block
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Tasks:
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- Image Classification
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Training Techniques:
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- Cosine Annealing
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- Random Erasing
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Training Data:
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- ImageNet
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ID: selecsls60
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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/selecsls.py#L342
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Weights: https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-selecsls/selecsls60-bbf87526.pth
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Results:
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- Task: Image Classification
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Dataset: ImageNet
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Metrics:
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Top 1 Accuracy: 77.99%
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Top 5 Accuracy: 93.83%
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- Name: selecsls60b
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In Collection: SelecSLS
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Metadata:
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FLOPs: 4657653144
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Parameters: 32770000
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File Size: 131252898
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Architecture:
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- Batch Normalization
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- Convolution
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- Dense Connections
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- Dropout
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- Global Average Pooling
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- ReLU
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- SelecSLS Block
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Tasks:
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- Image Classification
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Training Techniques:
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- Cosine Annealing
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- Random Erasing
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Training Data:
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- ImageNet
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ID: selecsls60b
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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/selecsls.py#L349
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Weights: https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-selecsls/selecsls60b-94e619b5.pth
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Results:
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- Task: Image Classification
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Dataset: ImageNet
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Metrics:
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Top 1 Accuracy: 78.41%
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Top 5 Accuracy: 94.18%
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-->
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