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A PyTorch implementation for PyramidNets (Deep Pyramidal Residual Networks, https://arxiv.org/abs/1610.02915)
The main features of dyhan0920/pyramidnet-pytorch are: Computer Vision Models, Image Classification Architectures, Model Implementations.
Projects with overlapping indexed features include: xternalz/wideresnet-pytorch — Wide Residual Networks (WideResNets) in PyTorch. prlz77/resnext.pytorch — Reproduces ResNet-V3 with pytorch. bamos/densenet.pytorch — A PyTorch implementation of DenseNet. aosokin/biogans. 1adrianb/face-alignment — This is a PyTorch-based computer vision library for detecting 2D and 3D facial landmark coordinates. It functions as a… 1zb/deformable-convolution-pytorch — PyTorch implementation of Deformable Convolution.
Wide Residual Networks (WideResNets) in PyTorch
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
