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PyTorch Implementation of Fully Convolutional Networks. (Training code to reproduce the original result is available.)
PyTorch implementation of Deformable Convolution
This is a PyTorch-based computer vision library for detecting 2D and 3D facial landmark coordinates. It functions as a facial landmark detector and reconstruction tool, utilizing deep learning to identify precise geometric points on human faces from image datasets. The library allows for the selection of specific detection backends to balance accuracy and processing speed. It supports the integration of precomputed bounding box files, which enables the system to bypass the initial detection phase and proceed directly to landmark extraction. The toolkit includes capabilities for batch image p
Base pretrained models and datasets in pytorch (MNIST, SVHN, CIFAR10, CIFAR100, STL10, AlexNet, VGG16, VGG19, ResNet, Inception, SqueezeNet)
The main features of isht7/pytorch-deeplab-resnet are: Computer Vision Models, Model Implementations, Segmentation Architectures.
Open-source alternatives to isht7/pytorch-deeplab-resnet include: wkentaro/pytorch-fcn — PyTorch Implementation of Fully Convolutional Networks. (Training code to reproduce the original result is available.). 1zb/deformable-convolution-pytorch — PyTorch implementation of Deformable Convolution. 1adrianb/face-alignment — This is a PyTorch-based computer vision library for detecting 2D and 3D facial landmark coordinates. It functions as a… amdegroot/ssd.pytorch — This is a PyTorch object detection framework that implements the Single Shot MultiBox Detector for identifying and… aaron-xichen/pytorch-playground — Base pretrained models and datasets in pytorch (MNIST, SVHN, CIFAR10, CIFAR100, STL10, AlexNet, VGG16, VGG19, ResNet,… aosokin/biogans.