Aug 10, 2020 · We develop a new approach to unsupervised deep metric learning where the network is learned based on self-supervision information across images instead of ...
Overview of the proposed approach for unsupervised deep metric learning with transformed attention consistency and contrastive clustering loss. 3 Method. 3.1 ...
Nov 27, 2020 · Overview of the proposed approach for unsupervised deep metric learning with transformed attention consistency and contrastive clustering loss.
In this work, we adapt the recent state-of-the-art multi-similarity (MS) loss [2] from supervised metric learning to unsupervised metric learning using k- ...
Unsupervised Deep Metric Learning with Transformed Attention ...
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This consistency leads to a pairwise self-supervision loss, allowing us to learn a Siamese deep neural network to encode and compare images against their ...
Aug 10, 2020 · A new approach to unsupervised deep metric learning where the network is learned based on self-supervision information across images instead ...
In this work, we explore the task of unsupervised metric learning. We propose to generate pseudo-labels for deep metric learning directly from the clustering ...
This paper presents a novel unsupervised deep metric learning approach, termed unsupervised collaborative metric learning with mixed-scale groups (MS-UGCML), ...
Unsupervised Deep Metric Learning with Transformed Attention Consistency and Contrastive Clustering Loss (ECCV) [paper]. The Group Loss for Deep Metric Learning ...
Unsupervised deep metric learning with transformed attention consistency and contrastive clustering loss. Y Li, S Kan, Z He. European Conference on Computer ...