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Found 5 papers, 2 papers with code
On Train-Test Class Overlap and Detection for Image Retrieval
How important is it for training and evaluation sets to not have class overlap in image retrieval?
SyncMask: Synchronized Attentional Masking for Fashion-centric Vision-Language Pretraining
Vision-language models (VLMs) have made significant strides in cross-modal understanding through large-scale paired datasets.
Conditional Cross Attention Network for Multi-Space Embedding without Entanglement in Only a SINGLE Network
Many studies in vision tasks have aimed to create effective embedding spaces for single-label object prediction within an image.
Boosting vision transformers for image retrieval
(4) We enhance locality of interactions at the deeper layers of the encoder, which is the relative weakness of vision transformers.
All the attention you need: Global-local, spatial-channel attention for image retrieval
Apart from backbone, training pipelines and loss functions, popular approaches have focused on different spatial pooling and attention mechanisms, which are at the core of learning a powerful global image representation.
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