NPR Effects Using the Geometry Shader. - Pedro Hermosilla; Pere-Pau Vázquez (GPU Pro, 2010)

Uncertainty Visualization of Brain Fibers. - Pedro Hermosilla; Ralph Brecheisen; Pere-Pau Vázquez; Anna Vilanova (CEIG, 2012)

Instant Visualization of Secondary Structures of Molecular Models. - Pedro Hermosilla; Victor Guallar; Àlvar Vinacua; Pere-Pau Vázquez (VCBM, 2015)

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)

High quality illustrative effects for molecular rendering. - Pedro Hermosilla; Victor Guallar; Àlvar Vinacua; Pere-Pau Vázquez (Comput. Graph., 2016)

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)

Interactive GPU-based generation of solvent-excluded surfaces. - Pedro Hermosilla; Michael Krone; Victor Guallar; Pere-Pau Vázquez; Àlvar Vinacua; Timo Ropinski (Vis. Comput., 2017)

Advanced inspection techniques for molecular simulations. - Pedro Hermosilla (2017)

Improving Perception of Molecular Surface Visualizations by Incorporating Translucency Effects. - Pedro Hermosilla; Sebastian Maisch; Pere-Pau Vázquez; Timo Ropinski (VCBM@MICCAI, 2018)

A General Illumination Model for Molecular Visualization. - Pedro Hermosilla; Pere-Pau Vázquez; Àlvar Vinacua; Timo Ropinski (Comput. Graph. Forum, 2018)

Visual Analysis of protein-ligand interactions. - Pere-Pau Vázquez; Pedro Hermosilla; Victor Guallar; Jorge Estrada; Àlvar Vinacua (Comput. Graph. Forum, 2018)

Monte Carlo convolution for learning on non-uniformly sampled point clouds. - Pedro Hermosilla; Tobias Ritschel 001; Pere-Pau Vázquez; Àlvar Vinacua; Timo Ropinski (ACM Trans. Graph., 2018)

Total Denoising: Unsupervised Learning of 3D Point Cloud Cleaning. - Pedro Hermosilla Casajus; Tobias Ritschel 001; Timo Ropinski (ICCV, 2019)

Deep-learning the Latent Space of Light Transport. - Pedro Hermosilla; Sebastian Maisch; Tobias Ritschel 001; Timo Ropinski (Comput. Graph. Forum, 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)

Real-Time Visualization of 3D Amyloid-Beta Fibrils from 2D Cryo-EM Density Maps. - Hannah Kniesel; Timo Ropinski; Pedro Hermosilla (VCBM, 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 001; Timo Ropinski (CoRR, 2020)

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 001; Timo Ropinski (ICLR, 2021)

Enabling Viewpoint Learning through Dynamic Label Generation. - Michael Schelling; Pedro Hermosilla; Pere-Pau Vázquez; Timo Ropinski (Comput. Graph. Forum, 2021)

Data-driven deep density estimation. - Patrik Puchert; Pedro Hermosilla; Tobias Ritschel 001; Timo Ropinski (Neural Comput. Appl., 2021)

Void Space Surfaces to Convey Depth in Vessel Visualizations. - Julian Kreiser; Pedro Hermosilla; Timo Ropinski (IEEE Trans. Vis. Comput. Graph., 2021)

Clean Implicit 3D Structure from Noisy 2D STEM Images. - Hannah Kniesel; Timo Ropinski; Tim Bergner; Kavitha Shaga Devan; Clarissa Read; Paul Walther; Tobias Ritschel 001; Pedro Hermosilla (CVPR, 2022)

RADU: Ray-Aligned Depth Update Convolutions for ToF Data Denoising. - Michael Schelling; Pedro Hermosilla; Timo Ropinski (CVPR, 2022)

Variance-Aware Weight Initialization for Point Convolutional Neural Networks. - Pedro Hermosilla; Michael Schelling; Tobias Ritschel 001; Timo Ropinski (ECCV (28), 2022)

Gaussian Mixture Convolution Networks. - Adam Celarek; Pedro Hermosilla; Bernhard Kerbl; Timo Ropinski; Michael Wimmer 001 (ICLR, 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)

Contrastive Representation Learning for 3D Protein Structures. - Pedro Hermosilla; Timo Ropinski (CoRR, 2022)

Weakly-Supervised Optical Flow Estimation for Time-of-Flight. - Michael Schelling; Pedro Hermosilla; Timo Ropinski (WACV, 2023)

ClusterNet: A Perception-Based Clustering Model for Scattered Data. - Sebastian Hartwig; Christian van Onzenoodt; Pedro Hermosilla; Timo Ropinski (CoRR, 2023)

Spatially Guiding Unsupervised Semantic Segmentation Through Depth-Informed Feature Distillation and Sampling. - Leon Sick; Dominik Engel; Pedro Hermosilla; Timo Ropinski (CoRR, 2023)

Point Neighborhood Embeddings. - Pedro Hermosilla (CoRR, 2023)

Lang3DSG: Language-based contrastive pre-training for 3D Scene Graph prediction. - Sebastian Koch; Pedro Hermosilla; Narunas Vaskevicius; Mirco Colosi; Timo Ropinski (3DV, 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 (CVPR, 2024)

Unsupervised Semantic Segmentation Through Depth-Guided Feature Correlation and Sampling. - Leon Sick; Dominik Engel; Pedro Hermosilla; Timo Ropinski (CVPR, 2024)

Weakly Supervised Virus Capsid Detection with Image-Level Annotations in Electron Microscopy Images. - Hannah Kniesel; Leon Sick; Tristan Payer; Tim Bergner; Kavitha Shaga Devan; Clarissa Read; Paul Walther; Timo Ropinski; Pedro Hermosilla (ICLR, 2024)

On the Importance of Local and Global Feature Learning for Automated Measurable Residual Disease Detection in Flow Cytometry Data. - Lisa Weijler; Michael Reiter; Pedro Hermosilla; Margarita Maurer-Granofszky; Michael N. Dworzak (ICPR (12), 2024)

SGRec3D: Self-Supervised 3D Scene Graph Learning via Object-Level Scene Reconstruction. - Sebastian Koch; Pedro Hermosilla; Narunas Vaskevicius; Mirco Colosi; Timo Ropinski (WACV, 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 (WACV, 2024)

G-Style: Stylized Gaussian Splatting. - Áron Samuel Kovács; Pedro Hermosilla; Renata G. Raidou (CoRR, 2024)

CutS3D: Cutting Semantics in 3D for 2D Unsupervised Instance Segmentation. - Leon Sick; Dominik Engel; Sebastian Hartwig; Pedro Hermosilla; Timo Ropinski (CoRR, 2024)

PPSurf: Combining Patches and Point Convolutions for Detailed Surface Reconstruction. - Philipp Erler; Lizeth J. Fuentes Perez; Pedro Hermosilla; Paul Guerrero 001; Renato Pajarola; Michael Wimmer 001 (Comput. Graph. Forum, 2024)

Surface-aware Mesh Texture Synthesis with Pre-trained 2D CNNs. - Áron Samuel Kovács; Pedro Hermosilla; Renata G. Raidou (Comput. Graph. Forum, 2024)

𝒢-Style: Stylized Gaussian Splatting. - Áron Samuel Kovács; Pedro Hermosilla; Renata G. Raidou (Comput. Graph. Forum, 2024)

Efficient Continuous Group Convolutions for Local SE(3) Equivariance in 3D Point Clouds. - Lisa Weijler; Pedro Hermosilla (3DV, 2025)

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 (3DV, 2025)

Masked Scene Modeling: Narrowing the Gap Between Supervised and Self-Supervised Learning in 3D Scene Understanding. - Pedro Hermosilla; Christian Stippel; Leon Sick (CVPR, 2025)

RelationField: Relate Anything in Radiance Fields. - Sebastian Koch; Johanna Wald; Mirco Colosi; Narunas Vaskevicius; Pedro Hermosilla; Federico Tombari; Timo Ropinski (CVPR, 2025)

Exploring Modality Guidance to Enhance VFM-based Feature Fusion for UDA in 3D Semantic Segmentation. - Johannes Spöcklberger; Wei Lin 019; Pedro Hermosilla; Sivan Doveh; Horst Possegger; Muhammad Jehanzeb Mirza (CVPR Workshops, 2025)

Attention-Guided Masked Autoencoders for Learning Image Representations. - Leon Sick; Dominik Engel; Pedro Hermosilla; Timo Ropinski (WACV, 2025)

HPSCAN: Human Perception-Based Scattered Data Clustering. - Sebastian Hartwig; Christian van Onzenoodt; Dominik Engel; Pedro Hermosilla; Timo Ropinski (Comput. Graph. Forum, 2025)

Active Learning Inspired ControlNet Guidance for Augmenting Semantic Segmentation Datasets. - Hannah Kniesel; Pedro Hermosilla; Timo Ropinski (CoRR, 2025)

Marching Neurons: Accurate Surface Extraction for Neural Implicit Shapes. - Christian Stippel; Felix Mujkanovic; Thomas Leimkühler; Pedro Hermosilla (CoRR, 2025)

Style Brush: Guided Style Transfer for 3D Objects. - Áron Samuel Kovács; Pedro Hermosilla; Renata G. Raidou (CoRR, 2025)

OpenHype: Hyperbolic Embeddings for Hierarchical Open-Vocabulary Radiance Fields. - Lisa Weijler; Sebastian Koch; Fabio Poiesi; Timo Ropinski; Pedro Hermosilla (CoRR, 2025)