1 citations · 2 across the 20 of their papers we have counts for
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Learning to See through Action: Predictive Curiosity for Robots
Stelios Zarifis, Panagiotis Filntisis, George Retsinas +1
Humans and animals do not learn vision from a fixed set of data: they move, interact, and learn from the visual consequences of their actions. Motivated by this developmental view,…
GLAM-SLAM: Real-time Gaussian Large-scale Mapping via Flow Densification and Spatial Decomposition
Panagiotis Mermigkas, Argyris Manetas, Petros Maragos
Existing Gaussian-splatting-based monocular Simultaneous Localization and Mapping (SLAM) systems are either tailored to short sequences, are not real-time, or suffer from prohibiti…
Uncertainty-Driven Anomaly Detection for Psychotic Relapse Using Smartwatches: Forecasting and Multi-Task Learning Fusion
Nikolaos Tsalkitzis, Panagiotis P. Filntisis, Petros Maragos +1
Digital phenotyping enables continuous passive monitoring of behavior and physiology, offering a promising paradigm for early detection of psychotic relapse. In this work, we devel…
Registration-Free Learnable Multi-View Capture of Faces in Dense Semantic Correspondence
Panagiotis P. Filntisis, George Retsinas, Radek Daněček +3
Recent frameworks like ToFu and TEMPEH provide an automated alternative to classical registration pipelines by predicting 3D meshes in dense semantic correspondence directly from c…
NTIRE 2026 Challenge on Video Saliency Prediction: Methods and Results
Andrey Moskalenko, Alexey Bryncev, Ivan Kosmynin +40
This paper presents an overview of the NTIRE 2026 Challenge on Video Saliency Prediction. The goal of the challenge participants was to develop automatic saliency map prediction me…
VGGT-HPE: Reframing Head Pose Estimation as Relative Pose Prediction
Vasiliki Vasileiou, Panagiotis P. Filntisis, Petros Maragos +1
Monocular head pose estimation is traditionally formulated as direct regression from a single image to an absolute pose. This paradigm forces the network to implicitly internalize…
Mind the Shape Gap: A Benchmark and Baseline for Deformation-Aware 6D Pose Estimation of Agricultural Produce
Nikolas Chatzis, Angeliki Tsinouka, Katerina Papadimitriou +7
Accurate 6D pose estimation for robotic harvesting is fundamentally hindered by the biological deformability and high intra-class shape variability of agricultural produce. Instanc…