Supervised Image Retrieval
3 papers with code • 1 benchmarks • 1 datasets
Most implemented papers
Unicom: Universal and Compact Representation Learning for Image Retrieval
To further enhance the low-dimensional feature representation, we randomly select partial feature dimensions when calculating the similarities between embeddings and class-wise prototypes.
Generalized Product Quantization Network for Semi-supervised Image Retrieval
Image retrieval methods that employ hashing or vector quantization have achieved great success by taking advantage of deep learning.
Self-Supervised Bernoulli Autoencoders for Semi-Supervised Hashing
This paper investigates the robustness of hashing methods based on variational autoencoders to the lack of supervision, focusing on two semi-supervised approaches currently in use.