78 citations · 145 across the 18 of their papers we have counts for
21 papers
Global Average Precision for Representation Learning
Bill Psomas, Mohammad Mahdi, Michalis Thomas +3
Standard information retrieval metrics, such as mean Average Precision (mAP), assess performance one query at a time, based on how the similarities between a query and its positive…
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…
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…
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…
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…
AMES: Asymmetric and Memory-Efficient Similarity Estimation for Instance-level Retrieval
Pavel Suma, Giorgos Kordopatis-Zilos, Ahmet Iscen +1
This work investigates the problem of instance-level image retrieval re-ranking with the constraint of memory efficiency, ultimately aiming to limit memory usage to 1KB per image.…
Fusion Transformer with Object Mask Guidance for Image Forgery Analysis
Dimitrios Karageorgiou, Giorgos Kordopatis-Zilos, Symeon Papadopoulos
In this work, we introduce OMG-Fuser, a fusion transformer-based network designed to extract information from various forensic signals to enable robust image forgery detection and…
The 2023 Video Similarity Dataset and Challenge
Ed Pizzi, Giorgos Kordopatis-Zilos, Hiral Patel +6
This work introduces a dataset, benchmark, and challenge for the problem of video copy detection and localization. The problem comprises two distinct but related tasks: determining…
Improving Synthetically Generated Image Detection in Cross-Concept Settings
Pantelis Dogoulis, Giorgos Kordopatis-Zilos, Ioannis Kompatsiaris +1
New advancements for the detection of synthetic images are critical for fighting disinformation, as the capabilities of generative AI models continuously evolve and can lead to hyp…
Self-Supervised Video Similarity Learning
Giorgos Kordopatis-Zilos, Giorgos Tolias, Christos Tzelepis +3
We introduce SVS, a video similarity learning approach with self-supervision. Self-Supervised Learning (SSL) is typically used to train deep models on a proxy task so as to hav…
A Multi-Stream Fusion Network for Image Splicing Localization
Maria Siopi, Giorgos Kordopatis-Zilos, Polychronis Charitidis +2
In this paper, we address the problem of image splicing localization with a multi-stream network architecture that processes the raw RGB image in parallel with other handcrafted fo…
InDistill: Information flow-preserving knowledge distillation for model compression
Ioannis Sarridis, Christos Koutlis, Giorgos Kordopatis-Zilos +2
In this paper, we introduce InDistill, a method that serves as a warmup stage for enhancing Knowledge Distillation (KD) effectiveness. InDistill focuses on transferring critical in…
The MeVer DeepFake Detection Service: Lessons Learnt from Developing and Deploying in the Wild
Spyridon Baxevanakis, Giorgos Kordopatis-Zilos, Panagiotis Galopoulos +6
Enabled by recent improvements in generation methodologies, DeepFakes have become mainstream due to their increasingly better visual quality, the increase in easy-to-use generation…
Leveraging Selective Prediction for Reliable Image Geolocation
Apostolos Panagiotopoulos, Giorgos Kordopatis-Zilos, Symeon Papadopoulos
Reliable image geolocation is crucial for several applications, ranging from social media geo-tagging to fake news detection. State-of-the-art geolocation methods surpass human per…
DnS: Distill-and-Select for Efficient and Accurate Video Indexing and Retrieval
Giorgos Kordopatis-Zilos, Christos Tzelepis, Symeon Papadopoulos +2
In this paper, we address the problem of high performance and computationally efficient content-based video retrieval in large-scale datasets. Current methods typically propose eit…
Leveraging EfficientNet and Contrastive Learning for Accurate Global-scale Location Estimation
Giorgos Kordopatis-Zilos, Panagiotis Galopoulos, Symeon Papadopoulos +1
In this paper, we address the problem of global-scale image geolocation, proposing a mixed classification-retrieval scheme. Unlike other methods that strictly tackle the problem as…
Operation-wise Attention Network for Tampering Localization Fusion
Polychronis Charitidis, Giorgos Kordopatis-Zilos, Symeon Papadopoulos +1
In this work, we present a deep learning-based approach for image tampering localization fusion. This approach is designed to combine the outcomes of multiple image forensics algor…
Audio-based Near-Duplicate Video Retrieval with Audio Similarity Learning
Pavlos Avgoustinakis, Giorgos Kordopatis-Zilos, Symeon Papadopoulos +2
In this work, we address the problem of audio-based near-duplicate video retrieval. We propose the Audio Similarity Learning (AuSiL) approach that effectively captures temporal pat…
Investigating the Impact of Pre-processing and Prediction Aggregation on the DeepFake Detection Task
Polychronis Charitidis, Giorgos Kordopatis-Zilos, Symeon Papadopoulos +1
Recent advances in content generation technologies (widely known as DeepFakes) along with the online proliferation of manipulated media content render the detection of such manipul…
ViSiL: Fine-grained Spatio-Temporal Video Similarity Learning
Giorgos Kordopatis-Zilos, Symeon Papadopoulos, Ioannis Patras +1
In this paper we introduce ViSiL, a Video Similarity Learning architecture that considers fine-grained Spatio-Temporal relations between pairs of videos -- such relations are typic…
FIVR: Fine-grained Incident Video Retrieval
Giorgos Kordopatis-Zilos, Symeon Papadopoulos, Ioannis Patras +1
This paper introduces the problem of Fine-grained Incident Video Retrieval (FIVR). Given a query video, the objective is to retrieve all associated videos, considering several type…