482 Open source projects that are alternatives of or similar to SCL

PyTorch implementation of the InfoNCE loss for self-supervised learning.

This is an official implementation for "SimMIM: A Simple Framework for Masked Image Modeling".

The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.

Parametric Instance Classification for Unsupervised Visual Feature Learning, NeurIPS 2020

AdCo: Adversarial Contrast for Efficient Learning of Unsupervised Representations from Self-Trained Negative Adversaries

Official PyTorch implementation of Contrastive Learning of Musical Representations

Object-aware Contrastive Learning for Debiased Scene Representation (NeurIPS 2021)

This is the code base for paper "G-SimCLR : Self-Supervised Contrastive Learning with Guided Projection via Pseudo Labelling" by Souradip Chakraborty, Aritra Roy Gosthipaty and Sayak Paul.

This repository contains the code implementation used in the paper Temporally Coherent Embeddings for Self-Supervised Video Representation Learning (TCE).

[NeurIPS 2021 Spotlight] Aligning Pretraining for Detection via Object-Level Contrastive Learning

PyTorch implementation of SimCLR: supports multi-GPU training and closely reproduces results

LibFewShot: A Comprehensive Library for Few-shot Learning.

Parametric Contrastive Learning (ICCV2021)

A curated list of awesome graph & self-supervised-learning-based recommendation.

Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习

S2-BNN: Bridging the Gap Between Self-Supervised Real and 1-bit Neural Networks via Guided Distribution Calibration (CVPR 2021)

Revisiting Contrastive Methods for Unsupervised Learning of Visual Representations. [NeurIPS 2021]

official implemntation for "Contrastive Learning with Stronger Augmentations"

SimCLRv2 - Big Self-Supervised Models are Strong Semi-Supervised Learners

[WACV'22] Code repository for the paper "Self-supervised Video Representation Learning with Cross-Stream Prototypical Contrasting", https://arxiv.org/abs/2106.10137.

Code for the paper "DisCont: Self-Supervised Visual Attribute Disentanglement using Context Vectors".

List of Publications in Graph Contrastive Learning

Generalized Deep Metric Learning.

[WWW 2021] Source code for "Graph Contrastive Learning with Adaptive Augmentation"

Sinkhorn Label Allocation is a label assignment method for semi-supervised self-training algorithms. The SLA algorithm is described in full in this ICML 2021 paper: https://arxiv.org/abs/2102.08622.

Official PyTorch code for CVPR 2020 paper "Deep Active Learning for Biased Datasets via Fisher Kernel Self-Supervision"

A TensorFlow implementation of Group Normalization on the task of image classification

Large Scale Fine-Grained Categorization and Domain-Specific Transfer Learning. CVPR 2018

Improved Residual Networks (https://arxiv.org/pdf/2004.04989.pdf)

A machine learning experiment

PyTorch implementation of "WILDCAT: Weakly Supervised Learning of Deep ConvNets for Image Classification, Pointwise Localization and Segmentation", CVPR 2017

ML data annotations made super easy for teams. Just upload data, add your team and build training/evaluation dataset in hours.

IPyPlot is a small python package offering fast and efficient plotting of images inside Python Notebooks. It's using IPython with HTML for faster, richer and more interactive way of displaying big numbers of images.

IdenProf dataset is a collection of images of identifiable professionals. It is been collected to enable the development of AI systems that can serve by identifying people and the nature of their job by simply looking at an image, just like humans can do.

Image classification for everyone.

Two-Stage Convolutional Neural Network for Breast Cancer Histology Image Classification. ICIAR 2018 Grand Challenge on BreAst Cancer Histology images (BACH)

Practice on cifar100(ResNet, DenseNet, VGG, GoogleNet, InceptionV3, InceptionV4, Inception-ResNetv2, Xception, Resnet In Resnet, ResNext,ShuffleNet, ShuffleNetv2, MobileNet, MobileNetv2, SqueezeNet, NasNet, Residual Attention Network, SENet, WideResNet)

finetune bert for small dataset text classification in a few-shot learning manner using ProtoNet

TensorFlow implementation of GoogLeNet and Inception for image classification.

Deep learning codes and projects using Python

Block-wisely Supervised Neural Architecture Search with Knowledge Distillation (CVPR 2020)

implement AlexNet with C / convolutional nerual network / machine learning / computer vision

Deep Learning API and Server in C++14 support for Caffe, Caffe2, PyTorch,TensorRT, Dlib, NCNN, Tensorflow, XGBoost and TSNE

Implementation of EfficientNet model. Keras and TensorFlow Keras.

A smart album for Android which use tensorflow to classify images

Accelerated deep learning R&D

Nudity detection with JavaScript and HTMLCanvas

🔥🔥NSFW implement in pytorch（色情图&性感图识别，本程序经过了线上大数据集测试，性能优异效果良好）🔥🔥

A curated list of deep learning image classification papers and codes

Code and Pretrained model for IGCV3

An example of using Tensorflow with Unity for image classification and object detection.

Bridging the gap Between Stability and Scalability in Neural Architecture Search

Traffic Sign Recognition with Keras.

📖 This guide is to help you understand the basics of the computerized image and develop computer vision projects with OpenCV. Includes Python, Java, JavaScript, C# and C++ examples.

A UI tool for quickly training image classifiers in the browser

A simple, flexible, and extensible template for PyTorch. It's beautiful.

🐰 Python lib for remo - the app for annotations and images management in Computer Vision

CNN image classifier implemented in Keras Notebook 🖼️.

Implementation of Transformer in Transformer, pixel level attention paired with patch level attention for image classification, in Pytorch

Detecting robot grasping positions with deep neural networks. The model is trained on Cornell Grasping Dataset. This is an implementation mainly based on the paper 'Real-Time Grasp Detection Using Convolutional Neural Networks' from Redmon and Angelova.