Simple demonstration of separable convolutions
A PyTorch implementation of Xception: Deep Learning with Depthwise Separable Convolutions
Spatiotemporal-separable 3D convolution network.
An implementation of Adaptive Separable Convolution for Video Frame Interpolation
Simple Speech Keyword Detecting with Depthwise Separable Convolutions | DLology
Lightweight CRNN for OCR (including handwritten text) with depthwise separable convolutions and spatial transformer module [keras+tf]
Implementation of Depthwise Separable Convolution (pytorch)
Convolutions for Sequence Modeling
Separable Subsurface Scattering is a technique that allows to efficiently perform subsurface scattering calculations in screen space in just two passes.
PyTorch code for the "Deep Neural Networks with Box Convolutions" paper
Cheng-Hao Tu, Jia-Hong Lee, Yi-Ming Chan and Chu-Song Chen, "Pruning Depthwise Separable Convolutions for MobileNet Compression," International Joint Conference on Neural Networks, IJCNN 2020, July 20...
Representation learning on large graphs using stochastic graph convolutions.
[ECCV 2022] SimpleRecon: 3D Reconstruction Without 3D Convolutions
Implementation of 1D, 2D, and 3D FFT convolutions in PyTorch. Much faster than direct convolutions for large kernel sizes.
#计算机科学#Convmelspec: Convertible Melspectrograms via 1D Convolutions
Implementation of YOLOv3-tiny + Depthwise Separable Convolution on FPGA
Experiments with Group Equivariant Convolutions in PyTorch
Code for reproducing results in "Glow: Generative Flow with Invertible 1x1 Convolutions"