PyTorch implementation of RetinaNet
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Updated
Apr 17, 2018 - Python
PyTorch implementation of RetinaNet
PyTorch implementation of focal loss for multi-class semantic segmentation
Implement RetinaNet with TensorFlow.eager
Pytorch implementation of Class Balanced Loss based on Effective number of Samples
Label Smoothing applied in Focal Loss
An unofficial implementation of ICCV 2017 RetinaNet (Focal Loss).
RetinaNet implementation in PyTorch
Multi-Label Image Classification of Chest X-Rays In Pytorch
Focal Loss of multi-classification in tensorflow
The implementation of focal loss proposed on "Focal Loss for Dense Object Detection" by KM He and support for multi-label dataset.
Generalized Focal Loss: Learning Qualified and Distributed Bounding Boxes for Dense Object Detection, NeurIPS2020
Implementation EfficientDet: Scalable and Efficient Object Detection in PyTorch
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