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Found 6 papers, 1 papers with code
Improving Deep Metric Learning with Virtual Classes and Examples Mining
In deep metric learning, the training procedure relies on sampling informative tuples.
DIABLO: Dictionary-based Attention Block for Deep Metric Learning
Recent breakthroughs in representation learning of unseen classes and examples have been made in deep metric learning by training at the same time the image representations and a corresponding metric with deep networks.
Metric Learning With HORDE: High-Order Regularizer for Deep Embeddings
Although the metric learning part is well addressed, this metric is usually computed over the average of the extracted deep features.
Ranked #18 on
Metric Learning
on CUB-200-2011
(using extra training data)
Efficient Codebook and Factorization for Second Order Representation Learning
Learning rich and compact representations is an open topic in many fields such as object recognition or image retrieval.
Leveraging Implicit Spatial Information in Global Features for Image Retrieval
Most image retrieval methods use global features that aggregate local distinctive patterns into a single representation.
Inverse Reinforcement Learning through Structured Classification
This paper adresses the inverse reinforcement learning (IRL) problem, that is inferring a reward for which a demonstrated expert behavior is optimal.
