EG 2025 - Posters

Permanent URI for this collection

https://diglib.eg.org/handle/10.2312/3607137
Table of Contents
Posters
Perspective Crop Based Egocentric Hand Pose Estimation via Fisheye Stereo Vision
[full paper Image] [meta data Image]
Hyejin Hur, Seongmin Baek, Younhee Gil, and Sangpil Kim
Sampling of Anisotropic Spatial Gaussians for Path Guiding
[full paper Image] [meta data Image]
Sergey Lelyakin, Vincent Schüßler, and Carsten Dachsbacher
Learning Proper Object Spacing with Polygon Rendering for Layout Rearrangement
[full paper Image] [meta data Image]
Kaifan Sun, Jun Xiao, and Haiyong Jiang
Cage-based Deformation of Field Functions
[full paper Image] [meta data Image]
Charline Grenier, Kevin Trancho, Cédric Zanni, and Loïc Barthe
A Gaze Prediction Model for Task-Oriented Virtual Reality
[full paper Image] [meta data Image]
Konstantina Mammou and Katerina Mania
VisibleUS: From Cryosectional Images to Real-Time Ultrasound Simulation
[full paper Image] [meta data Image]
Pablo Casanova-Salas, Jesus Gimeno, Arantxa Blasco-Serra, Eva María González-Soler, Laura Escamilla-Muñoz, Alfonso Amador Valverde-Navarro, Marcos Fernández, and Cristina Portalés
Automatic Image-Based Coral Polyp Analysis through Multi-View Instance Segmentation
[full paper Image] [meta data Image]
Somnath Dutta, Gaia Pavoni, Massimiliano Corsini, Fabio Ganovelli, Paolo Cignoni, Paolo Rossi, Elena Cenni, Roberto Simonini, Francesca Grassi, Davide Cassanelli, Stefano Cattini, Luigi Rovati, Alessandro Capra, and Cristina Castagnetti
Using Smartphone EXIF Data to Classify Lighting Conditions for Outdoor Augmented Reality
[full paper Image] [meta data Image]
Ivan Nikolov, Flavius-Alexandru Mircov, Jacob Holm Villumsen, Mike Lien Larsen, and Claus Madsen
NOVA-3DGS: No-reference Objective VAlidation for 3D Gaussian Splatting
[full paper Image] [meta data Image]
Valentina Piras, Amedeo Franco Bonatti, Carmelo De Maria, Paolo Cignoni, and Francesco Banterle
Weighted Feature Graph via Hierarchical Clustering
[full paper Image] [meta data Image]
Mathieu Ladeuil, Marc Trabucato, Alexis Vaisse, and Noura Faraj
Real-Time Rendering of Algebraic Surfaces
[full paper Image] [meta data Image]
Csongor Csanád Karikó and Gábor Valasek
Interactive Sketch-based Modeling of Braided Hair
[full paper Image] [meta data Image]
Hari Hara Gowtham Jetti and Amal Dev Parakkat
Visual Agentic System for Spatial Metric Query Answering in Remote Sensing Images
[full paper Image] [meta data Image]
Yinghao Wang and Cheng Wang

BibTeX (EG 2025 - Posters)
@inproceedings{
10.2312:egp.20251016,

booktitle = {
Eurographics 2025 - Posters},

editor = {
Günther, Tobias
 and 
Montazeri, Zahra
},
title = {{
Perspective Crop Based Egocentric Hand Pose Estimation via Fisheye Stereo Vision}},

author = {
Hur, Hyejin
 and 
Baek, Seongmin
 and 
Gil, Younhee
 and 
Kim, Sangpil
},
year = {
2025},

publisher = {
The Eurographics Association},


ISSN = {1017-4656},
ISBN = {978-3-03868-269-1},

DOI = {
10.2312/egp.20251016}

}
@inproceedings{
10.2312:egp.20251017,

booktitle = {
Eurographics 2025 - Posters},

editor = {
Günther, Tobias
 and 
Montazeri, Zahra
},
title = {{
Sampling of Anisotropic Spatial Gaussians for Path Guiding}},

author = {
Lelyakin, Sergey
 and 
Schüßler, Vincent
 and 
Dachsbacher, Carsten
},
year = {
2025},

publisher = {
The Eurographics Association},


ISSN = {1017-4656},
ISBN = {978-3-03868-269-1},

DOI = {
10.2312/egp.20251017}

}
@inproceedings{
10.2312:egp.20251018,

booktitle = {
Eurographics 2025 - Posters},

editor = {
Günther, Tobias
 and 
Montazeri, Zahra
},
title = {{
Learning Proper Object Spacing with Polygon Rendering for Layout Rearrangement}},

author = {
Sun, Kaifan
 and 
Xiao, Jun
 and 
Jiang, Haiyong
},
year = {
2025},

publisher = {
The Eurographics Association},


ISSN = {1017-4656},
ISBN = {978-3-03868-269-1},

DOI = {
10.2312/egp.20251018}

}
@inproceedings{
10.2312:egp.20251019,

booktitle = {
Eurographics 2025 - Posters},

editor = {
Günther, Tobias
 and 
Montazeri, Zahra
},
title = {{
Cage-based Deformation of Field Functions}},

author = {
Grenier, Charline
 and 
Trancho, Kevin
 and 
Zanni, Cédric
 and 
Barthe, Loïc
},
year = {
2025},

publisher = {
The Eurographics Association},


ISSN = {1017-4656},
ISBN = {978-3-03868-269-1},

DOI = {
10.2312/egp.20251019}

}
@inproceedings{
10.2312:egp.20251020,

booktitle = {
Eurographics 2025 - Posters},

editor = {
Günther, Tobias
 and 
Montazeri, Zahra
},
title = {{
A Gaze Prediction Model for Task-Oriented Virtual Reality}},

author = {
Mammou, Konstantina
 and 
Mania, Katerina
},
year = {
2025},

publisher = {
The Eurographics Association},


ISSN = {1017-4656},
ISBN = {978-3-03868-269-1},

DOI = {
10.2312/egp.20251020}

}
@inproceedings{
10.2312:egp.20251021,

booktitle = {
Eurographics 2025 - Posters},

editor = {
Günther, Tobias
 and 
Montazeri, Zahra
},
title = {{
VisibleUS: From Cryosectional Images to Real-Time Ultrasound Simulation}},

author = {
Casanova-Salas, Pablo
 and 
Gimeno, Jesus
 and 
Blasco-Serra, Arantxa
 and 
González-Soler, Eva María
 and 
Escamilla-Muñoz, Laura
 and 
Valverde-Navarro, Alfonso Amador
 and 
Fernández, Marcos
 and 
Portalés, Cristina
},
year = {
2025},

publisher = {
The Eurographics Association},


ISSN = {1017-4656},
ISBN = {978-3-03868-269-1},

DOI = {
10.2312/egp.20251021}

}
@inproceedings{
10.2312:egp.20251022,

booktitle = {
Eurographics 2025 - Posters},

editor = {
Günther, Tobias
 and 
Montazeri, Zahra
},
title = {{
Automatic Image-Based Coral Polyp Analysis through Multi-View Instance Segmentation}},

author = {
Dutta, Somnath
 and 
Pavoni, Gaia
 and 
Cattini, Stefano
 and 
Rovati, Luigi
 and 
Capra, Alessandro
 and 
Castagnetti, Cristina
 and 
Corsini, Massimiliano
 and 
Ganovelli, Fabio
 and 
Cignoni, Paolo
 and 
Rossi, Paolo
 and 
Cenni, Elena
 and 
Simonini, Roberto
 and 
Grassi, Francesca
 and 
Cassanelli, Davide
},
year = {
2025},

publisher = {
The Eurographics Association},


ISSN = {1017-4656},
ISBN = {978-3-03868-269-1},

DOI = {
10.2312/egp.20251022}

}
@inproceedings{
10.2312:egp.20251023,

booktitle = {
Eurographics 2025 - Posters},

editor = {
Günther, Tobias
 and 
Montazeri, Zahra
},
title = {{
Using Smartphone EXIF Data to Classify Lighting Conditions for Outdoor Augmented Reality}},

author = {
Nikolov, Ivan
 and 
Mircov, Flavius-Alexandru
 and 
Villumsen, Jacob Holm
 and 
Larsen, Mike Lien
 and 
Madsen, Claus
},
year = {
2025},

publisher = {
The Eurographics Association},


ISSN = {1017-4656},
ISBN = {978-3-03868-269-1},

DOI = {
10.2312/egp.20251023}

}
@inproceedings{
10.2312:egp.20251024,

booktitle = {
Eurographics 2025 - Posters},

editor = {
Günther, Tobias
 and 
Montazeri, Zahra
},
title = {{
NOVA-3DGS: No-reference Objective VAlidation for 3D Gaussian Splatting}},

author = {
Piras, Valentina
 and 
Bonatti, Amedeo Franco
 and 
Maria, Carmelo De
 and 
Cignoni, Paolo
 and 
Banterle, Francesco
},
year = {
2025},

publisher = {
The Eurographics Association},


ISSN = {1017-4656},
ISBN = {978-3-03868-269-1},

DOI = {
10.2312/egp.20251024}

}
@inproceedings{
10.2312:egp.20251025,

booktitle = {
Eurographics 2025 - Posters},

editor = {
Günther, Tobias
 and 
Montazeri, Zahra
},
title = {{
Weighted Feature Graph via Hierarchical Clustering}},

author = {
Ladeuil, Mathieu
 and 
Trabucato, Marc
 and 
Vaisse, Alexis
 and 
Faraj, Noura
},
year = {
2025},

publisher = {
The Eurographics Association},


ISSN = {1017-4656},
ISBN = {978-3-03868-269-1},

DOI = {
10.2312/egp.20251025}

}
@inproceedings{
10.2312:egp.20251026,

booktitle = {
Eurographics 2025 - Posters},

editor = {
Günther, Tobias
 and 
Montazeri, Zahra
},
title = {{
Real-Time Rendering of Algebraic Surfaces}},

author = {
Karikó, Csongor Csanád
 and 
Valasek, Gábor
},
year = {
2025},

publisher = {
The Eurographics Association},


ISSN = {1017-4656},
ISBN = {978-3-03868-269-1},

DOI = {
10.2312/egp.20251026}

}
@inproceedings{
10.2312:egp.20251027,

booktitle = {
Eurographics 2025 - Posters},

editor = {
Günther, Tobias
 and 
Montazeri, Zahra
},
title = {{
Interactive Sketch-based Modeling of Braided Hair}},

author = {
Jetti, Hari Hara Gowtham
 and 
Parakkat, Amal Dev
},
year = {
2025},

publisher = {
The Eurographics Association},


ISSN = {1017-4656},
ISBN = {978-3-03868-269-1},

DOI = {
10.2312/egp.20251027}

}
@inproceedings{
10.2312:egp.20251028,

booktitle = {
Eurographics 2025 - Posters},

editor = {
Günther, Tobias
 and 
Montazeri, Zahra
},
title = {{
Visual Agentic System for Spatial Metric Query Answering in Remote Sensing Images}},

author = {
Wang, Yinghao
 and 
Wang, Cheng
},
year = {
2025},

publisher = {
The Eurographics Association},


ISSN = {1017-4656},
ISBN = {978-3-03868-269-1},

DOI = {
10.2312/egp.20251028}

}
@inproceedings{
10.2312:egp.20252003,

booktitle = {
Eurographics 2025 - Posters},

editor = {
Günther, Tobias
 and 
Montazeri, Zahra
},
title = {{
EUROGRAPHICS 2025: Posters Frontmatter}},

author = {
Günther, Tobias
 and 
Montazeri, Zahra
},
year = {
2025},

publisher = {
Eurographics Association},


ISSN = {1017-4656},
ISBN = {978-3-03868-269-1},

DOI = {
10.2312/egp.20252003}

}

Browse

Recent Submissions

Now showing 1 - 14 of 14
  • Thumbnail Image
    Item
    Perspective Crop Based Egocentric Hand Pose Estimation via Fisheye Stereo Vision
    (The Eurographics Association, 2025) Hur, Hyejin; Baek, Seongmin; Gil, Younhee; Kim, Sangpil; Günther, Tobias; Montazeri, Zahra
    In this paper, we propose a method to improve the performance of hand pose estimation from egocentric view. To accurately capture hands moving within a wide range in daily activities, we mounted a fisheye stereo camera on a head mounted display to obtain wide-angle images from egocentric view. Our proposed two-stage method addresses the camera distortion introduced by this setup. The 2D hand keypoints estimated by stage-1 HandNet are converted into 3D hand keypoints through triangulation for perspective cropping. Stage-2 HandNet then predicts the final 2D hand keypoints from the undistorted hand crop image. To train stage-1 HandNet for perspective cropping, we built FisheyeEgoHAND dataset which consists of three categories of scenarios (separate hand, hand-hand, and hand-object) that reflect various hand interactions in an egocentric view. Through experiments, we demonstrated that two-stage 2D hand pose estimation outperforms one-stage approach without perspective cropping.
  • Thumbnail Image
    Item
    Sampling of Anisotropic Spatial Gaussians for Path Guiding
    (The Eurographics Association, 2025) Lelyakin, Sergey; Schüßler, Vincent; Dachsbacher, Carsten; Günther, Tobias; Montazeri, Zahra
    Directional models in path guiding struggle with representing parallax effects or anisotropic features. Our model instead describes the spatial distribution of a target vertex using a 3D Gaussian mixture model. While this dispenses with the need for reprojection and allows to represent anisotropic features easily, its directional probability density is not readily available, since it involves a marginal integral. In this work, we derive an expression for the PDF of our model in solid angle measure that is practical to evaluate. We demonstrate how our model can improve guiding accuracy in various scenes.
  • Thumbnail Image
    Item
    Learning Proper Object Spacing with Polygon Rendering for Layout Rearrangement
    (The Eurographics Association, 2025) Sun, Kaifan; Xiao, Jun; Jiang, Haiyong; Günther, Tobias; Montazeri, Zahra
    Successful scene arrangement requires ensuring appropriate distances between objects and avoiding excessive overlaps or separations. This work proposes a method for automatically learning spatial relationships between objects in scene arrangement using a differentiable renderer loss. First, objects surrounding a dominant item (e.g., a table in a dining room) are identified and represented as nodes in a polygon that encodes their spatial relations. The difference between the predicted and ground truth polygons is minimized via a rendering loss, which is integrated into the training of a generative diffusion model. This approach continuously optimizes the spatial distribution of objects during generation, ensuring physical consistency and practical usability. Experimental results show a significant reduction in collision rates compared to state-of-the-art methods.
  • Thumbnail Image
    Item
    Cage-based Deformation of Field Functions
    (The Eurographics Association, 2025) Grenier, Charline; Trancho, Kevin; Zanni, Cédric; Barthe, Loïc; Günther, Tobias; Montazeri, Zahra
    Implicit geometry is a popular representation for shape modelling. It provides several interesting properties, such as infinite resolution, continuity and smooth blending. However, implicit surfaces are difficult to deform as deformations need to be invertible. They are in general restricted to linear representations or more advanced translation-based deformations. We propose a method that adapts cage-based deformation to implicit surfaces while handling self-intersections in the deformed space.
  • Thumbnail Image
    Item
    A Gaze Prediction Model for Task-Oriented Virtual Reality
    (The Eurographics Association, 2025) Mammou, Konstantina; Mania, Katerina; Günther, Tobias; Montazeri, Zahra
    In this work, we present a gaze prediction model for Virtual Reality task-oriented environments. Unlike past work which focuses on gaze prediction for specific tasks, we investigate the role and potential of temporal continuity in enabling accurate predictions in diverse task categories. The model reduces input complexity while maintaining high prediction accuracy. Evaluated on the OpenNEEDS dataset, it significantly outperforms baseline methods. The model demonstrates strong potential for integration into gaze-based VR interactions and foveated rendering pipelines. Future work will focus on runtime optimization and expanding evaluation across diverse VR scenarios.
  • Thumbnail Image
    Item
    VisibleUS: From Cryosectional Images to Real-Time Ultrasound Simulation
    (The Eurographics Association, 2025) Casanova-Salas, Pablo; Gimeno, Jesus; Blasco-Serra, Arantxa; González-Soler, Eva María; Escamilla-Muñoz, Laura; Valverde-Navarro, Alfonso Amador; Fernández, Marcos; Portalés, Cristina; Günther, Tobias; Montazeri, Zahra
    The VisibleUS project aims to generate synthetic ultrasound images from cryosection images, focusing on the musculoskeletal system. Cryosection images provide a highly accurate representation of real tissue structures without artifacts. Using this rich anatomical data, we developed a ray-tracing-based simulation algorithm that models ultrasound wave propagation, scattering, and attenuation. This results in highly realistic ultrasound images that accurately depict fine anatomical details, such as muscle fibers and connective tissues. The simulation tool has various applications, including generating datasets for training neural networks and developing interactive training tools for ultrasound specialists. Its ability to produce realistic ultrasound images in real time enhances medical education and research, improving both the understanding and interpretation of ultrasound imaging.
  • Thumbnail Image
    Item
    Automatic Image-Based Coral Polyp Analysis through Multi-View Instance Segmentation
    (The Eurographics Association, 2025) Dutta, Somnath; Pavoni, Gaia; Corsini, Massimiliano; Ganovelli, Fabio; Cignoni, Paolo; Rossi, Paolo; Cenni, Elena; Simonini, Roberto; Grassi, Francesca; Cassanelli, Davide; Cattini, Stefano; Rovati, Luigi; Capra, Alessandro; Castagnetti, Cristina; Günther, Tobias; Montazeri, Zahra
    We present an automated framework for counting and measuring the polyps of Cladocora caespitosa, a Mediterranean reefbuilding coral. To our knowledge, the most practical method for counting polyps currently involves ecologists' visual inspection of a 3D model. However, measuring polyps from the model can lead to inaccuracies due to distortions in the reconstruction. Our method integrates deep learning-based instance segmentation on 2D images with 3D models for unique polyp identification, ensuring precise biometric extraction. The proposed pipeline automates polyp detection, counting, and measurement while overcoming the limitations of manual in situ methods. Laboratory validation demonstrates its accuracy and efficiency, paving the way for scalable, high-resolution phenotyping, and field monitoring of Mediterranean coral populations.
  • Thumbnail Image
    Item
    Using Smartphone EXIF Data to Classify Lighting Conditions for Outdoor Augmented Reality
    (The Eurographics Association, 2025) Nikolov, Ivan; Mircov, Flavius-Alexandru; Villumsen, Jacob Holm; Larsen, Mike Lien; Madsen, Claus; Günther, Tobias; Montazeri, Zahra
    Correctly matching real-world environment lighting conditions is an important step in making Augmented Reality content better fit with surrounding real objects. It is also the first step in larger, more complex problems like object relighting, shadow estimation, surface shading, etc. Dynamic classification of lighting conditions thus needs to be robust and lightweight. In this paper, we investigate the suitability of using pure EXIF data for classifying outdoor lighting conditions in four broad categories using a variety of shallow machine learning models. We gather a dataset of images together with EXIF metadata to test different models and show the results from the best-performing one in a real-time Augmented Reality application on a smartphone.
  • Thumbnail Image
    Item
    NOVA-3DGS: No-reference Objective VAlidation for 3D Gaussian Splatting
    (The Eurographics Association, 2025) Piras, Valentina; Bonatti, Amedeo Franco; Maria, Carmelo De; Cignoni, Paolo; Banterle, Francesco; Günther, Tobias; Montazeri, Zahra
    In recent years, radiance field methods, and in particular 3D Gaussian Splatting (3DGS), have distinguished themselves in the field of image-based rendering and scene reconstruction techniques, gaining significant success in academia and being cited in numerous research papers. Like other methods, 3DGS requires a large and diverse dataset of images for network training as a fundamental step to ensure effectiveness and high-quality results. Consequently, the acquisition phase is highly time-consuming, especially considering that a portion of the acquired dataset is not actually used for training but is reserved for testing. This is necessary because all commonly used metrics for evaluating the quality of 3D reconstructions, such as PSNR and SSIM, are reference-based metrics; i.e., requiring a ground truth. In this work, we present NOVA, a study focused on no-reference evaluation of 3DGS renders, based on key metrics in this field: PSNR and SSIM.
  • Thumbnail Image
    Item
    Weighted Feature Graph via Hierarchical Clustering
    (The Eurographics Association, 2025) Ladeuil, Mathieu; Trabucato, Marc; Vaisse, Alexis; Faraj, Noura; Günther, Tobias; Montazeri, Zahra
    In computer graphics, mesh clustering is a key component of various applications such as shape matching or skinning weight computation, especially when using hierarchical clustering. Garland et al. [GWH01] proposed to build a hierarchy of clusters by simplifying the dual graph of the mesh. We extend their method to provide control over cluster shapes through a combination of error metrics. Additionally, we alleviate the challenging task of finding an optimal threshold (stopping criterion) by considering a weighted feature graph that incorporates persistent cluster information throughout the hierarchy.
  • Thumbnail Image
    Item
    Real-Time Rendering of Algebraic Surfaces
    (The Eurographics Association, 2025) Karikó, Csongor Csanád; Valasek, Gábor; Günther, Tobias; Montazeri, Zahra
    We investigate the problem of robust and real-time rendering of algebraic surfaces. We show that expressing the intersection of the ray and the algebraic surface as a single univariate polynomial is not robust in practice, comparing results between monomial, Bernstein, Lagrange, and Chebyshev basis fits. We show that fitting multiple polynomials over subintervals, such as a unit length subdivision of the ray extent within the region of interest, improves robustness at a negligible performance cost.
  • Thumbnail Image
    Item
    Interactive Sketch-based Modeling of Braided Hair
    (The Eurographics Association, 2025) Jetti, Hari Hara Gowtham; Parakkat, Amal Dev; Günther, Tobias; Montazeri, Zahra
    Hair braids are widely used in various games and animated movies, thanks to their simplified representation and ease of animation. However, the existing research on modeling braids often relies on a limited dictionary of commonly seen hair braid patterns, constraining artists' ability to experiment by creating imaginary or creative hair braids. In this paper, we introduce a simple sketch-based interface for creating arbitrary hair braids. Our method employs a two-stage framework that first interprets a user-drawn sketch to extract the braid pattern. To accommodate arbitrarily drawn sketches, we then use a physics-inspired simulation to generate visually pleasing braids. In addition to automatically generating braids, our system allows users to interactively refine the braid pattern to create braids that match the user's imagination, facilitating experimentation and exploration of different braid structures.
  • Thumbnail Image
    Item
    Visual Agentic System for Spatial Metric Query Answering in Remote Sensing Images
    (The Eurographics Association, 2025) Wang, Yinghao; Wang, Cheng; Günther, Tobias; Montazeri, Zahra
    Accurately measuring real-world object dimensions from Remote Sensing (RS) images is crucial for applications in geospatial analysis and urban planning. Traditional Vision-Language Models (VLMs) struggle with spatial reasoning, while end-to-end remote sensing VLMs are often limited to predefined tasks such as image captioning. In this paper, we propose a visual agentic system for spatial metric query answering, dynamically integrating code-generation agents with a grounded remote sensing VLM and a Vision Specialist. Our system autonomously identifies reference objects, infers scale factors, and performs spatial measurements through structured subroutines. Experiments demonstrate that our approach achieves higher accuracy in footprint area estimation compared to state-of-the-art large language models with vision capabilities.
  • Thumbnail Image
    Item
    EUROGRAPHICS 2025: Posters Frontmatter
    (Eurographics Association, 2025) Günther, Tobias; Montazeri, Zahra; Günther, Tobias; Montazeri, Zahra