2 citations · 3 across the 9 of their papers we have counts for
20 papers · 1 filter
Instance-Level Composed Image Retrieval
Bill Psomas, George Retsinas, Nikos Efthymiadis +5
The progress of composed image retrieval (CIR), a popular research direction in image retrieval, where a combined visual and textual query is used, is held back by the absence of h…
Attention, Please! Revisiting Attentive Probing Through the Lens of Efficiency
Bill Psomas, Dionysis Christopoulos, Eirini Baltzi +6
As fine-tuning becomes impractical at scale, probing is emerging as the preferred evaluation protocol. However, standard linear probing can understate the capability of models whos…
Composed Image Retrieval for Training-Free Domain Conversion
Nikos Efthymiadis, Bill Psomas, Zakaria Laskar +4
This work addresses composed image retrieval in the context of domain conversion, where the content of a query image is retrieved in the domain specified by the query text. We show…
Boosting vision transformers for image retrieval
Chull Hwan Song, Jooyoung Yoon, Shunghyun Choi +1
Vision transformers have achieved remarkable progress in vision tasks such as image classification and detection. However, in instance-level image retrieval, transformers have not…
All the attention you need: Global-local, spatial-channel attention for image retrieval
Chull Hwan Song, Hye Joo Han, Yannis Avrithis
We address representation learning for large-scale instance-level image retrieval. Apart from backbone, training pipelines and loss functions, popular approaches have focused on di…
Few-shot learning via tensor hallucination
Michalis Lazarou, Yannis Avrithis, Tania Stathaki
Few-shot classification addresses the challenge of classifying examples given only limited labeled data. A powerful approach is to go beyond data augmentation, towards data synthes…