Implemenation of spatial transformers and explanation for the Vision transformers
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Updated
Oct 14, 2022 - Jupyter Notebook
Implemenation of spatial transformers and explanation for the Vision transformers
Spatial Transformer Networks (STN) implementation in TensorFlow
Classify traffic signs using traditional machine learning method and deep learning methods. [course project of "Media and Recognition"]
Sonar image registration by end to end unspuervised learning
Keras implementation of the spatial transformer network.
Spatial transformer CNN in tensorflow. Architecture explored in the early days of the project that led to idtracker.ai (www.idtracker.ai)
MNIST benchmarks with Spatial Transformer Networks, Vision Transformers and SpinalNets, with model modifications including CoordConv layers.
A Theano implementation of the paper "Spatial Transformer Networks" by Jaderberg et al..
Demo of deformable registration methods utilizing voxelmorph
机器学习
Tensorflow Implementation of DeepEmotion for Facial Expression Recognition
SCINet is a codebase for models that identify persistent facial skin conditions
Stanford CS 230 Group Project
Code for paper "Vis-IR Images Registration via Multi-scale Generative Adversial Network" Chao X.,Hanlin Z.,Ke Z.
A-Very-Deep-Spatial-Transformer-Towards-Robust-Single-Image-Super-Resolution
Large-scale 3D image registration based on spatial transformers and stacked convolutional autoencoders
pytorch STN implement for CUB200 dataset
Code for the paper: Foveated Convolutions: Improving Spatial Transformer Networks by Modelling the Retina
Tensorflow models for Spatial Transformer Networks
Spatial Transformer Networks with Affine, Projective and Elastic Transformations in Tensorflow
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