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Base pretrained models and datasets in pytorch (MNIST, SVHN, CIFAR10, CIFAR100, STL10, AlexNet, VGG16, VGG19, ResNet, Inception, SqueezeNet)
PyTorch implementation of Deformable Convolution
an implementation of Video Frame Interpolation via Adaptive Separable Convolution using PyTorch
The main features of sniklaus/pytorch-sepconv are: Convolutional Neural Networks (CNNs).
Open-source alternatives to sniklaus/pytorch-sepconv include: aaron-xichen/pytorch-playground — Base pretrained models and datasets in pytorch (MNIST, SVHN, CIFAR10, CIFAR100, STL10, AlexNet, VGG16, VGG19, ResNet,… automan000/convolution_lstm_pytorch. bamos/densenet.pytorch — A PyTorch implementation of DenseNet. bgshih/crnn — Convolutional Recurrent Neural Network. d-li14/octconv.pytorch. 1zb/deformable-convolution-pytorch — PyTorch implementation of Deformable Convolution.
