Search Results for author: Alexandros Stergiou

Found 16 papers, 13 papers with code

Every Shot Counts: Using Exemplars for Repetition Counting in Videos

1 code implementation26 Mar 2024 Saptarshi Sinha, Alexandros Stergiou, Dima Damen

We propose an exemplar-based approach that discovers visual correspondence of video exemplars across repetitions within target videos.

Holistic Representation Learning for Multitask Trajectory Anomaly Detection

1 code implementation3 Nov 2023 Alexandros Stergiou, Brent De Weerdt, Nikos Deligiannis

We encode temporally occluded trajectories, jointly learn latent representations of the occluded segments, and reconstruct trajectories based on expected motions across different temporal segments.

Anomaly Detection Representation Learning +1

Leaping Into Memories: Space-Time Deep Feature Synthesis

1 code implementation ICCV 2023 Alexandros Stergiou, Nikos Deligiannis

The success of deep learning models has led to their adaptation and adoption by prominent video understanding methods.

Video Understanding

Play It Back: Iterative Attention for Audio Recognition

1 code implementation20 Oct 2022 Alexandros Stergiou, Dima Damen

A key function of auditory cognition is the association of characteristic sounds with their corresponding semantics over time.

Audio Classification

The Wisdom of Crowds: Temporal Progressive Attention for Early Action Prediction

1 code implementation CVPR 2023 Alexandros Stergiou, Dima Damen

We propose a bottleneck-based attention model that captures the evolution of the action, through progressive sampling over fine-to-coarse scales.

Early Action Prediction

Efficient Modelling Across Time of Human Actions and Interactions

no code implementations5 Oct 2021 Alexandros Stergiou

The hierarchical extraction of features models variations of relatively similar classes the same as very dissimilar classes.

Action Recognition Video Understanding

The Mind's Eye: Visualizing Class-Agnostic Features of CNNs

1 code implementation29 Jan 2021 Alexandros Stergiou

Visual interpretability of Convolutional Neural Networks (CNNs) has gained significant popularity because of the great challenges that CNN complexity imposes to understanding their inner workings.

Multi-Temporal Convolutions for Human Action Recognition in Videos

1 code implementation8 Nov 2020 Alexandros Stergiou, Ronald Poppe

To address this challenge, we present a novel spatio-temporal convolution block that is capable of extracting spatio-temporal patterns at multiple temporal resolutions.

Action Recognition In Videos Temporal Action Localization +1

Learning Class Regularized Features for Action Recognition

no code implementations7 Feb 2020 Alexandros Stergiou, Ronald Poppe, Remco C. Veltkamp

We show that using Class Regularization blocks in state-of-the-art CNN architectures for action recognition leads to systematic improvement gains of 1. 8%, 1. 2% and 1. 4% on the Kinetics, UCF-101 and HMDB-51 datasets, respectively.

Action Recognition

Spatio-Temporal FAST 3D Convolutions for Human Action Recognition

no code implementations30 Sep 2019 Alexandros Stergiou, Ronald Poppe

Motivated by the often distinctive temporal characteristics of actions in either horizontal or vertical direction, we introduce a novel convolution block for CNN architectures with video input.

Action Recognition Temporal Action Localization

Class Feature Pyramids for Video Explanation

1 code implementation18 Sep 2019 Alexandros Stergiou, Georgios Kapidis, Grigorios Kalliatakis, Christos Chrysoulas, Ronald Poppe, Remco Veltkamp

We demonstrate the method on six state-of-the-art 3D convolution neural networks (CNNs) on three action recognition (Kinetics-400, UCF-101, and HMDB-51) and two egocentric action recognition datasets (EPIC-Kitchens and EGTEA Gaze+).

Action Recognition Temporal Action Localization

Analyzing Human-Human Interactions: A Survey

1 code implementation31 Jul 2018 Alexandros Stergiou, Ronald Poppe

The main challenges stem from dealing with the considerable variation in recording setting, the appearance of the people depicted and the coordinated performance of their interaction.

Action Recognition Temporal Action Localization

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