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Found 3 papers, 1 papers with code
Self-Supervised Ranking for Representation Learning
We present a new framework for self-supervised representation learning by formulating it as a ranking problem in an image retrieval context on a large number of random views (augmentations) obtained from images.
MIX'EM: Unsupervised Image Classification using a Mixture of Embeddings
We introduce three techniques to successfully train MIX'EM and avoid degenerate solutions; (i) diversify mixture components by maximizing entropy, (ii) minimize instance conditioned component entropy to enforce a clustered embedding space, and (iii) use an associative embedding loss to enforce semantic separability.
Mixture Dense Regression for Object Detection and Human Pose Estimation
We realize the framework for object detection and human pose estimation.
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