activity
20142026
most citedParticular object retrieval with integral max-pooling of CNN activations

677 citations · 769 across the 45 of their papers we have counts for

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Showing 2025 · cs.CVShow all

9 papers · 2 filters

cs.CV2025

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…

cs.CV2025

Instance-Level Generation for Representation Learning

Yankun Wu, Zakaria Laskar, Giorgos Kordopatis-Zilos +2

Instance-level recognition (ILR) focuses on identifying individual objects rather than broad categories, offering the highest granularity in image classification. However, this fin…

cs.CV2025

Category-level Text-to-Image Retrieval Improved: Bridging the Domain Gap with Diffusion Models and Vision Encoders

Faizan Farooq Khan, Vladan Stojnić, Zakaria Laskar +2

This work explores text-to-image retrieval for queries that specify or describe a semantic category. While vision-and-language models (VLMs) like CLIP offer a straightforward open-…

cs.CV2025

Processing and acquisition traces in visual encoders: What does CLIP know about your camera?

Ryan Ramos, Vladan Stojnić, Giorgos Kordopatis-Zilos +3

Prior work has analyzed the robustness of visual encoders to image transformations and corruptions, particularly in cases where such alterations are not seen during training. When…

cs.CV2025

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…

cs.CV2025

A Dataset for Semantic Segmentation in the Presence of Unknowns

Zakaria Laskar, Tomas Vojir, Matej Grcic +6

Before deployment in the real-world deep neural networks require thorough evaluation of how they handle both knowns, inputs represented in the training data, and unknowns (anomalie…

cs.CV2025

LOCORE: Image Re-ranking with Long-Context Sequence Modeling

Zilin Xiao, Pavel Suma, Ayush Sachdeva +4

We introduce LOCORE, Long-Context Re-ranker, a model that takes as input local descriptors corresponding to an image query and a list of gallery images and outputs similarity score…

cs.CV2025

LPOSS: Label Propagation Over Patches and Pixels for Open-vocabulary Semantic Segmentation

Vladan Stojnić, Yannis Kalantidis, Jiří Matas +1

We propose a training-free method for open-vocabulary semantic segmentation using Vision-and-Language Models (VLMs). Our approach enhances the initial per-patch predictions of VLMs…

cs.CV2025

ILIAS: Instance-Level Image retrieval At Scale

Giorgos Kordopatis-Zilos, Vladan Stojnić, Anna Manko +7

This work introduces ILIAS, a new test dataset for Instance-Level Image retrieval At Scale. It is designed to evaluate the ability of current and future foundation models and retri…