Pedro Hermosilla

According to our database, Pedro Hermosilla authored at least 39 papers between 2010 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

PPSurf: Combining Patches and Point Convolutions for Detailed Surface Reconstruction.

Philipp Erler, Lizeth J. Fuentes Perez, Pedro Hermosilla, Paul Guerrero, Renato Pajarola, Michael Wimmer

Comput. Graph. Forum, February, 2024

TTT-KD: Test-Time Training for 3D Semantic Segmentation through Knowledge Distillation from Foundation Models.

Lisa Weijler, Muhammad Jehanzeb Mirza, Leon Sick, Can Ekkazan, Pedro Hermosilla

CoRR, 2024

Surface-aware Mesh Texture Synthesis with Pre-trained 2D CNNs.

Áron Samuel Kovács, Pedro Hermosilla, Renata G. Raidou

CoRR, 2024

Attention-Guided Masked Autoencoders For Learning Image Representations.

Leon Sick, Dominik Engel, Pedro Hermosilla, Timo Ropinski

CoRR, 2024

Open3DSG: Open-Vocabulary 3D Scene Graphs from Point Clouds with Queryable Objects and Open-Set Relationships.

Sebastian Koch, Narunas Vaskevicius, Mirco Colosi, Pedro Hermosilla, Timo Ropinski

CoRR, 2024

FATE: Feature-Agnostic Transformer-based Encoder for learning generalized embedding spaces in flow cytometry data.

Lisa Weijler, Florian Kowarsch, Michael Reiter, Pedro Hermosilla, Margarita Maurer-Granofszky, Michael N. Dworzak

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

SGRec3D: Self-Supervised 3D Scene Graph Learning via Object-Level Scene Reconstruction.

Sebastian Koch, Pedro Hermosilla, Narunas Vaskevicius, Mirco Colosi, Timo Ropinski

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

2023

Lang3DSG: Language-based contrastive pre-training for 3D Scene Graph prediction.

Sebastian Koch, Pedro Hermosilla, Narunas Vaskevicius, Mirco Colosi, Timo Ropinski

CoRR, 2023

Point Neighborhood Embeddings.

Pedro Hermosilla

CoRR, 2023

Spatially Guiding Unsupervised Semantic Segmentation Through Depth-Informed Feature Distillation and Sampling.

Leon Sick, Dominik Engel, Pedro Hermosilla, Timo Ropinski

CoRR, 2023

ClusterNet: A Perception-Based Clustering Model for Scattered Data.

Sebastian Hartwig, Christian van Onzenoodt, Pedro Hermosilla, Timo Ropinski

CoRR, 2023

Weakly-Supervised Optical Flow Estimation for Time-of-Flight.

Michael Schelling, Pedro Hermosilla, Timo Ropinski

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

2022

Contrastive Representation Learning for 3D Protein Structures.

Pedro Hermosilla, Timo Ropinski

CoRR, 2022

Learning Human Viewpoint Preferences from Sparsely Annotated Models.

Sebastian Hartwig, Michael Schelling, Christian van Onzenoodt, Pere-Pau Vázquez, Pedro Hermosilla, Timo Ropinski

Comput. Graph. Forum, 2022

Gaussian Mixture Convolution Networks.

Adam Celarek, Pedro Hermosilla, Bernhard Kerbl, Timo Ropinski, Michael Wimmer

Proceedings of the Tenth International Conference on Learning Representations, 2022

Variance-Aware Weight Initialization for Point Convolutional Neural Networks.

Pedro Hermosilla, Michael Schelling, Tobias Ritschel, Timo Ropinski

Proceedings of the Computer Vision - ECCV 2022, 2022

RADU: Ray-Aligned Depth Update Convolutions for ToF Data Denoising.

Michael Schelling, Pedro Hermosilla, Timo Ropinski

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Clean Implicit 3D Structure from Noisy 2D STEM Images.

Hannah Kniesel, Timo Ropinski, Tim Bergner, Kavitha Shaga Devan, Clarissa Read, Paul Walther, Tobias Ritschel, Pedro Hermosilla

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

Void Space Surfaces to Convey Depth in Vessel Visualizations.

Julian Kreiser, Pedro Hermosilla, Timo Ropinski

IEEE Trans. Vis. Comput. Graph., 2021

Data-driven deep density estimation.

Patrik Puchert, Pedro Hermosilla, Tobias Ritschel, Timo Ropinski

Neural Comput. Appl., 2021

Enabling Viewpoint Learning through Dynamic Label Generation.

Michael Schelling, Pedro Hermosilla, Pere-Pau Vázquez, Timo Ropinski

Comput. Graph. Forum, 2021

Intrinsic-Extrinsic Convolution and Pooling for Learning on 3D Protein Structures.

Pedro Hermosilla, Marco Schäfer, Matej Lang, Gloria Fackelmann, Pere-Pau Vázquez, Barbora Kozlíková, Michael Krone, Tobias Ritschel, Timo Ropinski

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

ProteiNN: Intrinsic-Extrinsic Convolution and Pooling for Scalable Deep Protein Analysis.

Pedro Hermosilla, Marco Schäfer, Matej Lang, Gloria Fackelmann, Pere-Pau Vázquez, Barbora Kozlíková, Michael Krone, Tobias Ritschel, Timo Ropinski

CoRR, 2020

Real-Time Visualization of 3D Amyloid-Beta Fibrils from 2D Cryo-EM Density Maps.

Hannah Kniesel, Timo Ropinski, Pedro Hermosilla

Proceedings of the 10th Eurographics Workshop on Visual Computing for Biology and Medicine, 2020

2019

Visualization of Large Molecular Trajectories.

David Duran, Pedro Hermosilla, Timo Ropinski, Barbora Kozlíková, Àlvar Vinacua, Pere-Pau Vázquez

IEEE Trans. Vis. Comput. Graph., 2019

Deep-learning the Latent Space of Light Transport.

Pedro Hermosilla, Sebastian Maisch, Tobias Ritschel, Timo Ropinski

Comput. Graph. Forum, 2019

Total Denoising: Unsupervised Learning of 3D Point Cloud Cleaning.

Pedro Hermosilla Casajus, Tobias Ritschel, Timo Ropinski

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

2018

Monte Carlo convolution for learning on non-uniformly sampled point clouds.

Pedro Hermosilla, Tobias Ritschel, Pere-Pau Vázquez, Àlvar Vinacua, Timo Ropinski

ACM Trans. Graph., 2018

Visual Analysis of protein-ligand interactions.

Pere-Pau Vázquez, Pedro Hermosilla, Victor Guallar, Jorge Estrada, Àlvar Vinacua

Comput. Graph. Forum, 2018

A General Illumination Model for Molecular Visualization.

Pedro Hermosilla, Pere-Pau Vázquez, Àlvar Vinacua, Timo Ropinski

Comput. Graph. Forum, 2018

Improving Perception of Molecular Surface Visualizations by Incorporating Translucency Effects.

Pedro Hermosilla, Sebastian Maisch, Pere-Pau Vázquez, Timo Ropinski

Proceedings of the 8th Eurographics Workshop on Visual Computing for Biology and Medicine, 2018

2017

Advanced inspection techniques for molecular simulations.

Pedro Hermosilla

PhD thesis, 2017

Interactive GPU-based generation of solvent-excluded surfaces.

Pedro Hermosilla, Michael Krone, Victor Guallar, Pere-Pau Vázquez, Àlvar Vinacua, Timo Ropinski

Vis. Comput., 2017

Physics-Based Visual Characterization of Molecular Interaction Forces.

Pedro Hermosilla, Jorge Estrada, Victor Guallar, Timo Ropinski, Àlvar Vinacua, Pere-Pau Vázquez

IEEE Trans. Vis. Comput. Graph., 2017

2016

High quality illustrative effects for molecular rendering.

Pedro Hermosilla, Victor Guallar, Àlvar Vinacua, Pere-Pau Vázquez

Comput. Graph., 2016

Interactive inspection of complex multi-object industrial assemblies.

Oscar Argudo, Isaac Besora, Pere Brunet, Carles Creus, Pedro Hermosilla, Isabel Navazo, Àlvar Vinacua

Comput. Aided Des., 2016

2015

Instant Visualization of Secondary Structures of Molecular Models.

Pedro Hermosilla, Victor Guallar, Àlvar Vinacua, Pere-Pau Vázquez

Proceedings of the Eurographics Workshop on Visual Computing for Biology and Medicine, 2015

2012

Uncertainty Visualization of Brain Fibers.

Pedro Hermosilla, Ralph Brecheisen, Pere-Pau Vázquez, Anna Vilanova

Proceedings of the XXII Spanish Computer Graphics Conference, 2012

2010

NPR Effects Using the Geometry Shader.

Pedro Hermosilla, Pere-Pau Vázquez

Proceedings of the GPU Pro - Advanced Rendering Techniques., 2010