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ORCIDPedro Hermosilla
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2020 – today
- 2024
[j15]Philipp Erler
, Lizeth J. Fuentes Perez, Pedro Hermosilla, Paul Guerrero, Renato Pajarola, Michael Wimmer:
PPSurf: Combining Patches and Point Convolutions for Detailed Surface Reconstruction. Comput. Graph. Forum 43(1) (2024)- [j14]Áron Samuel Kovács, Pedro Hermosilla, Renata G. Raidou:
Surface-aware Mesh Texture Synthesis with Pre-trained 2D CNNs. Comput. Graph. Forum 43(2): i-iii (2024) - [c17]Sebastian Koch, Pedro Hermosilla, Narunas Vaskevicius, Mirco Colosi, Timo Ropinski:
Lang3DSG: Language-based contrastive pre-training for 3D Scene Graph prediction. 3DV 2024: 1037-1047 - [c16]Leon Sick, Dominik Engel, Pedro Hermosilla, Timo Ropinski:
Unsupervised Semantic Segmentation Through Depth-Guided Feature Correlation and Sampling. CVPR 2024: 3637-3646 - [c15]Sebastian Koch, Narunas Vaskevicius, Mirco Colosi, Pedro Hermosilla, Timo Ropinski:
Open3DSG: Open-Vocabulary 3D Scene Graphs from Point Clouds with Queryable Objects and Open-Set Relationships. CVPR 2024: 14183-14193 - [c14]Hannah Kniesel, Leon Sick, Tristan Payer, Tim Bergner, Kavitha Shaga Devan, Clarissa Read, Paul Walther, Timo Ropinski, Pedro Hermosilla:
Weakly Supervised Virus Capsid Detection with Image-Level Annotations in Electron Microscopy Images. ICLR 2024 - [c13]Sebastian Koch, Pedro Hermosilla, Narunas Vaskevicius, Mirco Colosi, Timo Ropinski:
SGRec3D: Self-Supervised 3D Scene Graph Learning via Object-Level Scene Reconstruction. WACV 2024: 3392-3402 - [c12]Lisa Weijler, Florian Kowarsch, Michael Reiter, Pedro Hermosilla, Margarita Maurer-Granofszky, Michael N. Dworzak:
FATE: Feature-Agnostic Transformer-based Encoder for learning generalized embedding spaces in flow cytometry data. WACV 2024: 7941-7949 - [i25]Philipp Erler, Lizeth J. Fuentes Perez, Pedro Hermosilla, Paul Guerrero, Renato Pajarola, Michael Wimmer:
PPSURF: Combining Patches and Point Convolutions for Detailed Surface Reconstruction. CoRR abs/2401.08518 (2024) - [i24]Sebastian Koch, Narunas Vaskevicius, Mirco Colosi, Pedro Hermosilla, Timo Ropinski:
Open3DSG: Open-Vocabulary 3D Scene Graphs from Point Clouds with Queryable Objects and Open-Set Relationships. CoRR abs/2402.12259 (2024) - [i23]Leon Sick, Dominik Engel, Pedro Hermosilla, Timo Ropinski:
Attention-Guided Masked Autoencoders For Learning Image Representations. CoRR abs/2402.15172 (2024) - [i22]Áron Samuel Kovács, Pedro Hermosilla, Renata G. Raidou:
Surface-aware Mesh Texture Synthesis with Pre-trained 2D CNNs. CoRR abs/2403.06855 (2024) - [i21]Lisa Weijler, Muhammad Jehanzeb Mirza, Leon Sick, Can Ekkazan, Pedro Hermosilla:
TTT-KD: Test-Time Training for 3D Semantic Segmentation through Knowledge Distillation from Foundation Models. CoRR abs/2403.11691 (2024) - [i20]Áron Samuel Kovács, Pedro Hermosilla, Renata G. Raidou:
G-Style: Stylized Gaussian Splatting. CoRR abs/2408.15695 (2024) - 2023
- [c11]Michael Schelling, Pedro Hermosilla, Timo Ropinski:
Weakly-Supervised Optical Flow Estimation for Time-of-Flight. WACV 2023: 2134-2143 - [i19]Sebastian Hartwig, Christian van Onzenoodt, Pedro Hermosilla, Timo Ropinski:
ClusterNet: A Perception-Based Clustering Model for Scattered Data. CoRR abs/2304.14185 (2023) - [i18]Leon Sick, Dominik Engel, Pedro Hermosilla, Timo Ropinski:
Spatially Guiding Unsupervised Semantic Segmentation Through Depth-Informed Feature Distillation and Sampling. CoRR abs/2309.12378 (2023) - [i17]Sebastian Koch, Pedro Hermosilla, Narunas Vaskevicius, Mirco Colosi, Timo Ropinski:
SGRec3D: Self-Supervised 3D Scene Graph Learning via Object-Level Scene Reconstruction. CoRR abs/2309.15702 (2023) - [i16]Pedro Hermosilla:
Point Neighborhood Embeddings. CoRR abs/2310.02083 (2023) - [i15]Sebastian Koch, Pedro Hermosilla, Narunas Vaskevicius, Mirco Colosi, Timo Ropinski:
Lang3DSG: Language-based contrastive pre-training for 3D Scene Graph prediction. CoRR abs/2310.16494 (2023) - [i14]Lisa Weijler, Florian Kowarsch, Michael Reiter, Pedro Hermosilla, Margarita Maurer-Granofszky, Michael N. Dworzak:
FATE: Feature-Agnostic Transformer-based Encoder for learning generalized embedding spaces in flow cytometry data. CoRR abs/2311.03314 (2023) - 2022
- [j13]Sebastian Hartwig, Michael Schelling, Christian van Onzenoodt, Pere-Pau Vázquez, Pedro Hermosilla, Timo Ropinski:
Learning Human Viewpoint Preferences from Sparsely Annotated Models. Comput. Graph. Forum 41(6): 453-466 (2022) - [c10]Michael Schelling, Pedro Hermosilla, Timo Ropinski:
RADU: Ray-Aligned Depth Update Convolutions for ToF Data Denoising. CVPR 2022: 661-670 - [c9]Hannah Kniesel, Timo Ropinski, Tim Bergner, Kavitha Shaga Devan, Clarissa Read, Paul Walther, Tobias Ritschel, Pedro Hermosilla:
Clean Implicit 3D Structure from Noisy 2D STEM Images. CVPR 2022: 20730-20740 - [c8]Pedro Hermosilla, Michael Schelling, Tobias Ritschel, Timo Ropinski:
Variance-Aware Weight Initialization for Point Convolutional Neural Networks. ECCV (28) 2022: 74-89 - [c7]Adam Celarek, Pedro Hermosilla, Bernhard Kerbl, Timo Ropinski, Michael Wimmer:
Gaussian Mixture Convolution Networks. ICLR 2022 - [i13]Adam Celarek, Pedro Hermosilla, Bernhard Kerbl, Timo Ropinski, Michael Wimmer:
Gaussian Mixture Convolution Networks. CoRR abs/2202.09153 (2022) - [i12]Hannah Kniesel, Timo Ropinski, Tim Bergner, Kavitha Shaga Devan, Clarissa Read, Paul Walther, Tobias Ritschel, Pedro Hermosilla:
Clean Implicit 3D Structure from Noisy 2D STEM Images. CoRR abs/2203.15434 (2022) - [i11]Pedro Hermosilla, Timo Ropinski:
Contrastive Representation Learning for 3D Protein Structures. CoRR abs/2205.15675 (2022) - [i10]Michael Schelling, Pedro Hermosilla, Timo Ropinski:
Weakly-Supervised Optical Flow Estimation for Time-of-Flight. CoRR abs/2210.05298 (2022) - 2021
- [j12]Michael Schelling, Pedro Hermosilla, Pere-Pau Vázquez, Timo Ropinski:
Enabling Viewpoint Learning through Dynamic Label Generation. Comput. Graph. Forum 40(2): 413-423 (2021) - [j11]Patrik Puchert, Pedro Hermosilla, Tobias Ritschel, Timo Ropinski:
Data-driven deep density estimation. Neural Comput. Appl. 33(23): 16773-16807 (2021) - [j10]Julian Kreiser, Pedro Hermosilla, Timo Ropinski:
Void Space Surfaces to Convey Depth in Vessel Visualizations. IEEE Trans. Vis. Comput. Graph. 27(10): 3913-3925 (2021) - [c6]Pedro Hermosilla, Marco Schäfer, Matej Lang, Gloria Fackelmann, Pere-Pau Vázquez, Barbora Kozlíková, Michael Krone, Tobias Ritschel, Timo Ropinski:
Intrinsic-Extrinsic Convolution and Pooling for Learning on 3D Protein Structures. ICLR 2021 - [i9]Patrik Puchert, Pedro Hermosilla, Tobias Ritschel, Timo Ropinski:
Data-driven deep density estimation. CoRR abs/2107.11085 (2021) - [i8]Michael Schelling, Pedro Hermosilla, Timo Ropinski:
RADU: Ray-Aligned Depth Update Convolutions for ToF Data Denoising. CoRR abs/2111.15513 (2021) - [i7]Pedro Hermosilla, Michael Schelling, Tobias Ritschel, Timo Ropinski:
Variance-Aware Weight Initialization for Point Convolutional Neural Networks. CoRR abs/2112.03777 (2021) - 2020
- [c5]Hannah Kniesel, Timo Ropinski, Pedro Hermosilla:
Real-Time Visualization of 3D Amyloid-Beta Fibrils from 2D Cryo-EM Density Maps. VCBM 2020: 115-125 - [i6]Michael Schelling, Pedro Hermosilla, Pere-Pau Vázquez, Timo Ropinski:
Enabling Viewpoint Learning through Dynamic Label Generation. CoRR abs/2003.04651 (2020) - [i5]Pedro Hermosilla, Marco Schäfer, Matej Lang, Gloria Fackelmann, Pere-Pau Vázquez, Barbora Kozlíková, Michael Krone, Tobias Ritschel, Timo Ropinski:
ProteiNN: Intrinsic-Extrinsic Convolution and Pooling for Scalable Deep Protein Analysis. CoRR abs/2007.06252 (2020)
2010 – 2019
- 2019
- [j9]Pedro Hermosilla, Sebastian Maisch, Tobias Ritschel, Timo Ropinski:
Deep-learning the Latent Space of Light Transport. Comput. Graph. Forum 38(4): 207-217 (2019) - [j8]David Duran, Pedro Hermosilla, Timo Ropinski, Barbora Kozlíková, Àlvar Vinacua, Pere-Pau Vázquez:
Visualization of Large Molecular Trajectories. IEEE Trans. Vis. Comput. Graph. 25(1): 987-996 (2019) - [c4]Pedro Hermosilla Casajus, Tobias Ritschel, Timo Ropinski:
Total Denoising: Unsupervised Learning of 3D Point Cloud Cleaning. ICCV 2019: 52-60 - [i4]Pedro Hermosilla, Tobias Ritschel, Timo Ropinski:
Total Denoising: Unsupervised Learning of 3D Point Cloud Cleaning. CoRR abs/1904.07615 (2019) - 2018
- [j7]Pedro Hermosilla, Pere-Pau Vázquez, Àlvar Vinacua, Timo Ropinski:
A General Illumination Model for Molecular Visualization. Comput. Graph. Forum 37(3): 367-378 (2018) - [j6]Pere-Pau Vázquez, Pedro Hermosilla, Victor Guallar, Jorge Estrada, Àlvar Vinacua:
Visual Analysis of protein-ligand interactions. Comput. Graph. Forum 37(3): 391-402 (2018) - [j5]Pedro Hermosilla, Tobias Ritschel, Pere-Pau Vázquez, Àlvar Vinacua, Timo Ropinski:
Monte Carlo convolution for learning on non-uniformly sampled point clouds. ACM Trans. Graph. 37(6): 235 (2018) - [c3]Pedro Hermosilla, Sebastian Maisch, Pere-Pau Vázquez, Timo Ropinski:
Improving Perception of Molecular Surface Visualizations by Incorporating Translucency Effects. VCBM@MICCAI 2018: 185-195 - [i3]Pedro Hermosilla, Tobias Ritschel, Pere-Pau Vázquez, Àlvar Vinacua, Timo Ropinski:
Monte Carlo Convolution for Learning on Non-Uniformly Sampled Point Clouds. CoRR abs/1806.01759 (2018) - [i2]Julian Kreiser, Pedro Hermosilla, Timo Ropinski:
Void Space Surfaces to Convey Depth in Vessel Visualizations. CoRR abs/1806.07729 (2018) - [i1]Pedro Hermosilla, Sebastian Maisch, Tobias Ritschel, Timo Ropinski:
Deep-learning the Latent Space of Light Transport. CoRR abs/1811.04756 (2018) - 2017
- [b1]Pedro Hermosilla:
Advanced inspection techniques for molecular simulations. Polytechnic University of Catalonia, Spain, 2017 - [j4]Pedro Hermosilla, Jorge Estrada, Victor Guallar, Timo Ropinski, Àlvar Vinacua, Pere-Pau Vázquez:
Physics-Based Visual Characterization of Molecular Interaction Forces. IEEE Trans. Vis. Comput. Graph. 23(1): 731-740 (2017) - [j3]Pedro Hermosilla, Michael Krone, Victor Guallar, Pere-Pau Vázquez, Àlvar Vinacua, Timo Ropinski:
Interactive GPU-based generation of solvent-excluded surfaces. Vis. Comput. 33(6-8): 869-881 (2017) - 2016
- [j2]Oscar Argudo, Isaac Besora, Pere Brunet, Carles Creus, Pedro Hermosilla, Isabel Navazo, Àlvar Vinacua:
Interactive inspection of complex multi-object industrial assemblies. Comput. Aided Des. 79: 48-59 (2016) - [j1]Pedro Hermosilla, Victor Guallar, Àlvar Vinacua, Pere-Pau Vázquez:
High quality illustrative effects for molecular rendering. Comput. Graph. 54: 113-120 (2016) - 2015
- [c2]Pedro Hermosilla, Victor Guallar, Àlvar Vinacua, Pere-Pau Vázquez:
Instant Visualization of Secondary Structures of Molecular Models. VCBM 2015: 51-60 - 2012
- [c1]Pedro Hermosilla, Ralph Brecheisen, Pere-Pau Vázquez, Anna Vilanova:
Uncertainty Visualization of Brain Fibers. CEIG 2012: 31-40 - 2010
- [p1]Pedro Hermosilla, Pere-Pau Vázquez:
NPR Effects Using the Geometry Shader. GPU Pro 2010: 140-165
Coauthor Index
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last updated on 2024-10-07 21:18 CEST by the dblp team
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