activity
20152026
most citedA Review on Deep Learning Techniques for Video Prediction

312 citations · 384 across the 28 of their papers we have counts for

collaborators

34 papers

cs.CV2026

Understanding Multimodal Complementarity for Single-Frame Action Anticipation

Manuel Benavent-Lledo, Konstantinos Bacharidis, Konstantinos Papoutsakis +2

Human action anticipation is commonly treated as a video understanding problem, implicitly assuming that dense temporal information is required to reason about future actions. In t…

cs.CV2026

OCCAM: Class-Agnostic, Training-Free, Prior-Free and Multi-Class Object Counting

Michail Spanakis, Iason Oikonomidis, Antonis Argyros

Class-Agnostic object Counting (CAC) involves counting instances of objects from arbitrary classes within an image. Due to its practical importance, CAC has received increasing att…

cs.CV2026

Combining Facial Videos and Biosignals for Stress Estimation During Driving

Paraskevi Valergaki, Vassilis C. Nicodemou, Iason Oikonomidis +2

Reliable stress recognition is critical in applications such as medical monitoring and safety-critical systems, including real-world driving. While stress is commonly detected usin…

cs.CV2025

Action Anticipation at a Glimpse: To What Extent Can Multimodal Cues Replace Video?

Manuel Benavent-Lledo, Konstantinos Bacharidis, Victoria Manousaki +3

Anticipating actions before they occur is a core challenge in action understanding research. While conventional methods rely on extracting and aggregating temporal information from…

cs.CV2025

Vision-Based Mistake Analysis in Procedural Activities: A Review of Advances and Challenges

Konstantinos Bacharidis, Antonis A. Argyros

Mistake analysis in procedural activities is a critical area of research with applications spanning industrial automation, physical rehabilitation, education and human-robot collab…

cs.CV2025

Enhancing Monocular 3D Hand Reconstruction with Learned Texture Priors

Giorgos Karvounas, Nikolaos Kyriazis, Iason Oikonomidis +2

We revisit the role of texture in monocular 3D hand reconstruction, not as an afterthought for photorealism, but as a dense, spatially grounded cue that can actively support pose a…

cs.GR2025

Reflections on Diversity: A Real-time Virtual Mirror for Inclusive 3D Face Transformations

Paraskevi Valergaki, Antonis Argyros, Giorgos Giannakakis +1

Real-time 3D face manipulation has significant applications in virtual reality, social media and human-computer interaction. This paper introduces a novel system, which we call Mir…

cs.CV2024

Y-MAP-Net: Real-time depth, normals, segmentation, multi-label captioning and 2D human pose in RGB images

Ammar Qammaz, Nikolaos Vasilikopoulos, Iason Oikonomidis +1

We present Y-MAP-Net, a Y-shaped neural network architecture designed for real-time multi-task learning on RGB images. Y-MAP-Net, simultaneously predicts depth, surface normals, hu…

cs.CV2024

D-PoSE: Depth as an Intermediate Representation for 3D Human Pose and Shape Estimation

Nikolaos Vasilikopoulos, Drosakis Drosakis, Antonis Argyros

We present D-PoSE (Depth as an Intermediate Representation for 3D Human Pose and Shape Estimation), a one-stage method that estimates human pose and SMPL-X shape parameters from a…

cs.CV2024★ 3 cited

Enhancing Action Recognition by Leveraging the Hierarchical Structure of Actions and Textual Context

Manuel Benavent-Lledo, David Mulero-Pérez, David Ortiz-Perez +2

We propose a novel approach to improve action recognition by exploiting the hierarchical organization of actions and by incorporating contextualized textual information, including…

cs.CV2024

ENACT: Entropy-based Clustering of Attention Input for Reducing the Computational Needs of Object Detection Transformers

Giorgos Savathrakis, Antonis Argyros

Transformers demonstrate competitive performance in terms of precision on the problem of vision-based object detection. However, they require considerable computational resources d…

cs.CV2024

Anticipating Object State Changes in Long Procedural Videos

Victoria Manousaki, Konstantinos Bacharidis, Filippos Gouidis +3

In this work, we introduce (a) the new problem of anticipating object state changes in images and videos during procedural activities, (b) new curated annotation data for object st…

cs.AI2024★ 10 cited

Fusing Domain-Specific Content from Large Language Models into Knowledge Graphs for Enhanced Zero Shot Object State Classification

Filippos Gouidis, Katerina Papantoniou, Konstantinos Papoutsakis +3

Domain-specific knowledge can significantly contribute to addressing a wide variety of vision tasks. However, the generation of such knowledge entails considerable human labor and…

cs.CV2023★ 2 cited

Recognizing Unseen States of Unknown Objects by Leveraging Knowledge Graphs

Filipos Gouidis, Konstantinos Papoutsakis, Theodore Patkos +2

We investigate the problem of Object State Classification (OSC) as a zero-shot learning problem. Specifically, we propose the first Object-agnostic State Classification (OaSC) meth…

cs.CV2023

TAPE: Temporal Attention-based Probabilistic human pose and shape Estimation

Nikolaos Vasilikopoulos, Nikos Kolotouros, Aggeliki Tsoli +1

Reconstructing 3D human pose and shape from monocular videos is a well-studied but challenging problem. Common challenges include occlusions, the inherent ambiguities in the 2D to…

cs.CV2022

Graphing the Future: Activity and Next Active Object Prediction using Graph-based Activity Representations

Victoria Manousaki, Konstantinos Papoutsakis, Antonis Argyros

We present a novel approach for the visual prediction of human-object interactions in videos. Rather than forecasting the human and object motion or the future hand-object contact…

cs.CV2021

PE-former: Pose Estimation Transformer

Paschalis Panteleris, Antonis Argyros

Vision transformer architectures have been demonstrated to work very effectively for image classification tasks. Efforts to solve more challenging vision tasks with transformers re…

cs.CV2021

Detecting Object States vs Detecting Objects: A New Dataset and a Quantitative Experimental Study

Filippos Gouidis, Theodore Patkos, Antonis Argyros +1

The detection of object states in images (State Detection - SD) is a problem of both theoretical and practical importance and it is tightly interwoven with other important computer…

cs.NE2021★ 3 cited

Even Faster SNN Simulation with Lazy+Event-driven Plasticity and Shared Atomics

Dennis Bautembach, Iason Oikonomidis, Antonis Argyros

We present two novel optimizations that accelerate clock-based spiking neural network (SNN) simulators. The first one targets spike timing dependent plasticity (STDP). It combines…

cs.CV2021★ 1 cited

Multi-view Image-based Hand Geometry Refinement using Differentiable Monte Carlo Ray Tracing

Giorgos Karvounas, Nikolaos Kyriazis, Iason Oikonomidis +2

The amount and quality of datasets and tools available in the research field of hand pose and shape estimation act as evidence to the significant progress that has been made.Howeve…

cs.CV2021

H-GAN: the power of GANs in your Hands

Sergiu Oprea, Giorgos Karvounas, Pablo Martinez-Gonzalez +7

We present HandGAN (H-GAN), a cycle-consistent adversarial learning approach implementing multi-scale perceptual discriminators. It is designed to translate synthetic images of han…

cs.NE2021★ 9 cited

Multi-GPU SNN Simulation with Static Load Balancing

Dennis Bautembach, Iason Oikonomidis, Antonis Argyros

We present a SNN simulator which scales to millions of neurons, billions of synapses, and 8 GPUs. This is made possible by 1) a novel, cache-aware spike transmission algorithm 2) a…

cs.CV2020★ 312 cited

A Review on Deep Learning Techniques for Video Prediction

Sergiu Oprea, Pablo Martinez-Gonzalez, Alberto Garcia-Garcia +4

The ability to predict, anticipate and reason about future outcomes is a key component of intelligent decision-making systems. In light of the success of deep learning in computer…

cs.CV2019★ 9 cited

A Review on Intelligent Object Perception Methods Combining Knowledge-based Reasoning and Machine Learning

Filippos Gouidis, Alexandros Vassiliades, Theodore Patkos +3

Object perception is a fundamental sub-field of Computer Vision, covering a multitude of individual areas and having contributed high-impact results. While Machine Learning has bee…