160 Open source projects that are alternatives of or similar to CLMR

Genre Classification using Convolutional Neural Networks

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

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

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

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

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

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

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

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

Generalized Deep Metric Learning.

official implemntation for "Contrastive Learning with Stronger Augmentations"

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

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

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

Parametric Instance Classification for Unsupervised Visual Feature Learning, NeurIPS 2020

📄 Spatial Contrastive Learning for Few-Shot Classification (ECML/PKDD 2021).

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

List of Publications in Graph Contrastive Learning

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

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

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

[ICRA 2020] Train generalizable policies for kit assembly with self-supervised dense correspondence learning.

[NeurIPS 2021] COCO-LM: Correcting and Contrasting Text Sequences for Language Model Pretraining

Code for EMNLP 2021 paper "Topic-Aware Contrastive Learning for Abstractive Dialogue Summarization"

Tensorflow Implementation for paper "self-supervised generative adversarial networks"

Code and resources on scalable and efficient Graph Neural Networks

Tutorial covering Open Source tools for Source Separation.

[CVPR 2020] Action Segmentation with Joint Self-Supervised Temporal Domain Adaptation (PyTorch)

Vector Quantized Autoregressive Predictive Coding (VQ-APC)

A JavaScript module for searching music scores.

code for our ECCV-2020 paper: Self-supervised Video Representation Learning by Pace Prediction

A C++ Library for Audio Analysis

Implementation of Barlow Twins paper

LiBai(李白): A Toolbox for Large-Scale Distributed Parallel Training

Olaf: Overly Lightweight Acoustic Fingerprinting is a portable acoustic fingerprinting system.

DALI: a large Dataset of synchronised Audio, LyrIcs and vocal notes.

List of articles related to deep learning applied to music

🔉 spafe: Simplified Python Audio Features Extraction

A PyTorch implementation of "SelfGNN: Self-supervised Graph Neural Networks without explicit negative sampling" paper, which appeared in The International Workshop on Self-Supervised Learning for the Web (SSL'21) @ the Web Conference 2021 (WWW'21).

Omniscient Mozart, being able to transcribe everything in the music, including vocal, drum, chord, beat, instruments, and more.

Collection of datasets used for Optical Music Recognition

Fast and simple music and audio analysis using RNN in Python 🕵️‍♀️ 🥁

A toolkit for symbolic music generation

A semantic and technical analysis of musical scores based on Information Retrieval Principles

TKDE 22. CCCL: Contrastive Cascade Graph Learning.

The code for the ISMIR 2019 paper “Supervised symbolic music style translation using synthetic data”.

C++ library for audio and music analysis, description and synthesis, including Python bindings

Easily access song lyrics from Genius in a tibble.

Neural Relation Understanding: neural cardinality estimators for tabular data

FMA: A Dataset For Music Analysis

Network Analysis of Generalized Musical Spaces

The code for the MaD TwinNet. Demo page:

🎹 symbolic musical datasets

Matlab scripts accompanying the book "An Introduction to Audio Content Analysis" (www.AudioContentAnalysis.org)

Music Synthesis with Python talk, originally given at PyGotham 2017.

Source code for "Vocal melody extraction with semantic segmentation and audio-symbolic domain transfer learning".

PyTorch implementation of EMAN for self-supervised and semi-supervised learning: https://arxiv.org/abs/2101.08482

A Dataset for Cover Song Identification and Understanding

Video Representation Learning by Recognizing Temporal Transformations. In ECCV, 2020.