Aggregated Residual Transformations for Deep Neural Networks Our models, named ResNeXt, are the foundations of our entry to the ILSVRC 2016 classification task in which we secured 2nd place We further investigate ResNeXt on an ImageNet-5K set and the COCO detection set, also showing better results than its ResNet counterpart
ResNext – PyTorch Resnext models were proposed in Aggregated Residual Transformations for Deep Neural Networks Here we have the 2 versions of resnet models, which contains 50, 101 layers repspectively