Comments (2)
Hi.
All quality indicators in the README tables are revalued by me. If the mark Training
is not indicated in the Remarks
field, then the model is converted. Usually the conversion requires a little additional training of the model, since I use standard normalization for all models, but the original models often use custom preprocessing.
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@osmr ,
Okey.
Since the original mxnet repo on github did not contain retrain module and this module is not open-source but important to reproduce performance, i will directly cite the acc value on the paper.
Thanks for your answer.
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Related Issues (20)
- API
- Inplace RunError when testing backward of RevNet with PyTorch 1.11.0 HOT 1
- [PyTorch] simplepose_resnet18_coco model weights loading error
- [Pytorch] Could you provide the hyper-parameters for the model training on Pascal VOC dataset?
- Adding new SOTA backbones
- Issue while using seresnet HOT 1
- (tf)Resnesta model problems HOT 12
- demo_pt.py failed on ICNet HOT 4
- Error in PSPBlock while running inference with ICNet HOT 2
- Problem when loading CGNet HOT 3
- Looking forward to the <nfnets> researched by deepmind
- 'seresnext50_32x4d' pytorch RuntimeError: Given input size: (2048x4x4). Calculated output size: (2048x-2x-2). Output size is too small HOT 1
- Multiple outputs using PSPNet pre-trained model on Cityscapes HOT 7
- VoVNet27s Model Weights Missing HOT 1
- Performance issues in your project (by P3) HOT 1
- Visual Transformers?
- VGG models for cifar
- pytorchcv in_size argument
- PyramidNet maybe wrong.
- Support the XDG Base Directory Specification
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