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20172023
most citedChallenges in Disentangling Independent Factors of Variation

32 citations · 117 across the 14 of their papers we have counts for

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11 papers · 1 filter

cs.CV2023★ 1 cited

Unpaired Translation from Semantic Label Maps to Images by Leveraging Domain-Specific Simulations

Lin Zhang, Tiziano Portenier, Orcun Goksel

Photorealistic image generation from simulated label maps are necessitated in several contexts, such as for medical training in virtual reality. With conventional deep learning met…

cs.CV2021★ 3 cited

Generative Feature-driven Image Replay for Continual Learning

Kevin Thandiackal, Tiziano Portenier, Andrea Giovannini +2

Neural networks are prone to catastrophic forgetting when trained incrementally on different tasks. Popular incremental learning methods mitigate such forgetting by retaining a sub…

cs.CV2021

Probabilistic Spatial Analysis in Quantitative Microscopy with Uncertainty-Aware Cell Detection using Deep Bayesian Regression of Density Maps

Alvaro Gomariz, Tiziano Portenier, César Nombela-Arrieta +1

3D microscopy is key in the investigation of diverse biological systems, and the ever increasing availability of large datasets demands automatic cell identification methods that n…

cs.CV2021

Utilizing Uncertainty Estimation in Deep Learning Segmentation of Fluorescence Microscopy Images with Missing Markers

Alvaro Gomariz, Raphael Egli, Tiziano Portenier +2

Fluorescence microscopy images contain several channels, each indicating a marker staining the sample. Since many different marker combinations are utilized in practice, it has bee…

cs.CV2020★ 19 cited

Modality Attention and Sampling Enables Deep Learning with Heterogeneous Marker Combinations in Fluorescence Microscopy

Alvaro Gomariz, Tiziano Portenier, Patrick M. Helbling +4

Fluorescence microscopy allows for a detailed inspection of cells, cellular networks, and anatomical landmarks by staining with a variety of carefully-selected markers visualized a…

cs.CV2020★ 14 cited

GramGAN: Deep 3D Texture Synthesis From 2D Exemplars

Tiziano Portenier, Siavash Bigdeli, Orcun Goksel

We present a novel texture synthesis framework, enabling the generation of infinite, high-quality 3D textures given a 2D exemplar image. Inspired by recent advances in natural text…

cs.CV2020

Deep Image Translation for Enhancing Simulated Ultrasound Images

Lin Zhang, Tiziano Portenier, Christoph Paulus +1

Ultrasound simulation based on ray tracing enables the synthesis of highly realistic images. It can provide an interactive environment for training sonographers as an educational t…

cs.CV2018★ 1 cited

Specular-to-Diffuse Translation for Multi-View Reconstruction

Shihao Wu, Hui Huang, Tiziano Portenier +4

Most multi-view 3D reconstruction algorithms, especially when shape-from-shading cues are used, assume that object appearance is predominantly diffuse. To alleviate this restrictio…

cs.CV2018★ 24 cited

FaceShop: Deep Sketch-based Face Image Editing

Tiziano Portenier, Qiyang Hu, Attila Szabó +3

We present a novel system for sketch-based face image editing, enabling users to edit images intuitively by sketching a few strokes on a region of interest. Our interface features…

cs.CV2017★ 32 cited

Challenges in Disentangling Independent Factors of Variation

Attila Szabó, Qiyang Hu, Tiziano Portenier +2

We study the problem of building models that disentangle independent factors of variation. Such models could be used to encode features that can efficiently be used for classificat…

cs.CV2017★ 12 cited

Disentangling Factors of Variation by Mixing Them

Qiyang Hu, Attila Szabó, Tiziano Portenier +2

We propose an approach to learn image representations that consist of disentangled factors of variation without exploiting any manual labeling or data domain knowledge. A factor of…