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Self-supervised Learning of Pose Embeddings from Spatiotemporal Relations in Videos
Ömer Sümer, Tobias Dencker, Björn Ommer
Human pose analysis is presently dominated by deep convolutional networks trained with extensive manual annotations of joint locations and beyond. To avoid the need for expensive l…
Unsupervised Video Understanding by Reconciliation of Posture Similarities
Timo Milbich, Miguel Bautista, Ekaterina Sutter +1
Understanding human activity and being able to explain it in detail surpasses mere action classification by far in both complexity and value. The challenge is thus to describe an a…
Deep Unsupervised Similarity Learning using Partially Ordered Sets
Miguel A Bautista, Artsiom Sanakoyeu, Björn Ommer
Unsupervised learning of visual similarities is of paramount importance to computer vision, particularly due to lacking training data for fine-grained similarities. Deep learning o…