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masked-ViGAT Public
Code and materials for our paper: D. Daskalakis, N. Gkalelis, V. Mezaris, "Masked Feature Modelling for the unsupervised pre-training of a Graph Attention Network block for bottom-up video event re…
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Gated-ViGAT Public
Gated-ViGAT. Code and data for our paper: N. Gkalelis, D. Daskalakis, V. Mezaris, "Gated-ViGAT: Efficient bottom-up event recognition and explanation using a new frame selection policy and gating m…
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TAME Public
Code and data for our learning-based eXplainable AI (XAI) method TAME: M. Ntrougkas, N. Gkalelis, V. Mezaris, "TAME: Attention Mechanism Based Feature Fusion for Generating Explanation Maps of Conv…
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ViGAT Public
This repository hosts the scripts and some of the pre-trained models presented in out paper "ViGAT: Bottom-up event recognition and explanation in video using factorized graph attention network", I…
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L-CAM Public
Code for our paper "Learning Visual Explanations for DCNN-Based Image Classifiers Using an Attention Mechanism", by I. Gkartzonika, N. Gkalelis, V. Mezaris, presented and included in the Proceeding…
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TextToVideoRetrieval-TtimesV Public
A PyTorch Implementation of the T x V model from "Are all combinations equal? Combining textual and visual features with multiple space learning for text-based video retrieval", Proc. ECCVW 2022.
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RetargetVid Public
Video dataset and code for transforming a video's aspect ratio, from our papers "A fast smart-cropping method and dataset for video retargeting", IEEE ICIP 2021, and "A Web Service for Video Smart-…
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ObjectGraphs Public
This repository hosts the code and data for our paper "ObjectGraphs: Using Objects and a Graph Convolutional Network for the Bottom-up Recognition and Explanation of Events in Video", Proc. 2nd Int…
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Structured Pruning of LSTMs via Eigenanalysis and Geometric Median. This code can be used for generating more compact LSTMs, which is very useful for mobile multimedia applications and deep learnin…
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In this work, a novel pruning framework is introduced to compress noisy or less discriminant filters in small fractional steps, in deep convolutional networks. The proposed framework utilizes a cla…
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[ACM ICMR 2020] Attention Mechanisms, Signal Encodings and Fusion Strategies for Improved Ad-hoc Video Search with Dual Encoding Networks
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fully_convolutional_networks Public
Implementation of various fully convolutional networks in Keras
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