MoCo v2 is an improved version of the Momentum Contrast self-supervised learning algorithm. Motivated by the findings presented in the SimCLR paper, authors:
These modifications enable MoCo to outperform the state-of-the-art SimCLR with a smaller batch size and fewer epochs.
Source: Improved Baselines with Momentum Contrastive LearningPaper | Code | Results | Date | Stars |
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Task | Papers | Share |
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Self-Supervised Learning | 16 | 22.54% |
Image Classification | 7 | 9.86% |
Semantic Segmentation | 6 | 8.45% |
Object Detection | 5 | 7.04% |
Classification | 3 | 4.23% |
Language Modelling | 2 | 2.82% |
Instance Segmentation | 2 | 2.82% |
Self-Supervised Image Classification | 2 | 2.82% |
Clustering | 2 | 2.82% |
Component | Type |
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Feedforward Network
|
Feedforward Networks | |
InfoNCE
|
Loss Functions | |
Random Gaussian Blur
|
Image Data Augmentation |