SOP is a non-parametric self-supervised learning method that represents each visual prototype by an anchor plus its k nearest-neighbor support embeddings, improving ImageNet and transfer benchmarks over iBOT and DINO.
Deep clustering for unsupervised learning of visual features
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CV 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Self-Organizing Visual Prototypes for Non-Parametric Representation Learning
SOP is a non-parametric self-supervised learning method that represents each visual prototype by an anchor plus its k nearest-neighbor support embeddings, improving ImageNet and transfer benchmarks over iBOT and DINO.