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Found 4 papers, 4 papers with code
Optimization of Rank Losses for Image Retrieval
It provides an upperbound for rank losses and ensures robust training.
Hybrid Energy Based Model in the Feature Space for Out-of-Distribution Detection
HEAT complements prior density estimators of the ID density, e. g. parametric models like the Gaussian Mixture Model (GMM), to provide an accurate yet robust density estimation.
Hierarchical Average Precision Training for Pertinent Image Retrieval
Image Retrieval is commonly evaluated with Average Precision (AP) or Recall@k. Yet, those metrics, are limited to binary labels and do not take into account errors' severity.
Ranked #1 on
Metric Learning
on DyML-Animal
Robust and Decomposable Average Precision for Image Retrieval
In image retrieval, standard evaluation metrics rely on score ranking, e. g. average precision (AP).
Ranked #2 on
Image Retrieval
on CUB-200-2011
