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scalismo

Scalable Image Analysis and Shape Modelling

scanner

Efficient video analysis at scale

scanners-box

The toolbox of open source scanners - 安全行业从业者自研开源扫描器合辑

scannertools

Python video processing toolkit

sceneparsing

Development kit for MIT Scene Parsing Benchmark

scigen

An automatic paper generator

scikit-learn

scikit-learn: machine learning in Python

scn_matlab

Matlab reimplementation of SCNSR

score_sde

Official code for Score-Based Generative Modeling through Stochastic Differential Equations (ICLR 2021, Oral)

score_sde_pytorch

PyTorch implementation for Score-Based Generative Modeling through Stochastic Differential Equations (ICLR 2021, Oral)

sdbe

Boosting Occluded Image Classification via Subspace Decomposition Based Estimation of Deep Features

seetafaceengine

segment-anything

The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

segnet-tutorial

Files for a tutorial to train SegNet for road scenes using the CamVid dataset

selective_search_ijcv_with_python

Simple Python script to compute Selective Search proposals in Matlab.

semantic-segmentation-pytorch

Pytorch implementation for Semantic Segmentation/Scene Parsing on MIT ADE20K dataset

semantic-segmentation-suite

Semantic Segmentation Suite in TensorFlow. Implement, train, and test new Semantic Segmentation models easily!

senet

Squeeze-and-Excitation Networks

seq2seq-mapping

example code for Sequence to Sequence mapping using encoder-decoder RNNs using dpnn and rnn libraries

seqgan

Implementation of Sequence Generative Adversarial Nets with Policy Gradient

sequence_gan

Generative adversarial networks (GAN) applied to sequential data via recurrent neural networks (RNN).

sequential-imagenet-dataloader

A plug-in replacement for DataLoader to load ImageNet disk-sequentially in PyTorch.

sferes2

A lightweight, generic C++ framework for evolutionary computation

sha

Hardware and Software Implementation of SHA Algorithm

sharesnet

ShaResNet: reducing residual network parameter number by sharing weights

shufflenet

ShuffleNet in PyTorch. Based on https://arxiv.org/abs/1707.01083

shunted-transformer

siamese-fc

State-of-the-art performance in arbitrary object tracking at 50-100 FPS with Fully Convolutional Siamese networks.

siamese-triplet

Siamese and triplet networks with online pair/triplet mining in PyTorch

siamese_net

This package shows how to train a siamese network using Lasagne and Theano and includes network definitions for state-of-the-art networks including: DeepID, DeepID2, Chopra et. al, and Hani et. al. We also include one pre-trained model using a custom convolutional network.