HobbitLong/CMC

Health v2 · maintenance only

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Adoption not part of the score

1340 stars · 179 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Official PyTorch implementation of Contrastive Multiview Coding (CMC), a self-supervised visual representation learning method that contrasts multiple views of data, plus unofficial implementations of MoCo and Instance Discrimination. It is research code accompanying an arXiv 2019 paper for training ResNets and AlexNet on ImageNet.

Use cases

• train self-supervised image representations with contrastive learning
• reproduce CMC, MoCo, or InsDis results on ImageNet
• study how the number of contrasted views affects representation quality
• compare contrastive vs predictive objectives for unsupervised learning
• get pretrained weights for instance discrimination and momentum contrast models
• benchmark unsupervised methods against supervised AlexNet on ImageNet classification

When to choose

• you need reference implementations of CMC, MoCo, or InsDis for research or reproduction
• you want to experiment with multiview contrastive learning in PyTorch
• you need pretrained self-supervised backbone weights from these methods

When to avoid

• you need a maintained production library with recent framework support
• you want a general-purpose self-supervised learning framework rather than paper-specific code
• you require support for PyTorch versions beyond what the repo was tested with

Facets

library · maturity maintenance

machine-learning deep-learning machine-learning computer-vision deep-learning python self-supervised-learning contrastive-learning pytorch representation-learning research-code moco instance-discrimination linux gpu

Member repositories

For agents

markdown · JSON · MCP: product_card(name="HobbitLong/CMC")