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Short Bio Welcome! I'm a Computer Scientist at CONICET and an Assistant Professor at Universidad Torcuato Di Tella, Argentina. I'm a former postdoc from IST Austria - Bernd Bickel's group. I've got my Ph.D. at GRAPHDECO group, INRIA Sophia Antipolis, France. In 2012 I've graduated as a Systems Engineer from UNICEN University, Tandil, Argentina. My research interests focus on developing AI tools for 2D and 3D content manipulation.
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Miguel Fainstein, Viviana Siless, Emmanuel Iarussi
In recent years, there has been a growing interest in training Neural Networks to approximate Unsigned Distance Fields (UDFs) for representing open surfaces in the context of 3D reconstruction.However, UDFs are non-differentiable at the zero level set which leads to significant errors in distances and gradients, generally resulting in [...]
Paula Feldman, Miguel Fainstein, Viviana Siless, Claudio Delrieux, Emmanuel Iarussi
We present a data-driven generative framework for synthesizing blood vessel 3D geometry. This is a challenging task due to the complexity of vascular systems, which are highly variating in shape, size, and structure. Existing model-based methods provide some degree of control and variation in the structures produced [...]
Duilio Deangeli, Emmanuel Iarussi, Juan Pablo Princich, Mariana Bendersky, Ignacio Larrabide, José Ignacio Orlando
Although normal homologous brain structures are approximately symmetrical by definition, they also have shape differences due to e.g. natural ageing. On the other hand, neurodegenerative conditions induce their own changes in this asymmetry, making them more pronounced [...]
Felix S. L. Thomsen, Emmanuel Iarussi, Jan Borggrefe, Steven K. Boyd, Yue Wang, Michele C. Battié
This study aims to provide a reliable method for the generation of realistic bone microstructure, serving for the training of neural networks and the development of new diagnostic parameters of bone architecture and mineralization. In a first step, we trained a volumetric generative model in a progressive manner to create patches of realistic bone [...]
Duilio Deangeli, Francisco Iarussi, Hernán Külsgaard, Delfina Braggio, Juan Pablo Princich, Mariana Bendersky, Emmanuel Iarussi, Ignacio Larrabide, José Ignacio Orlando
Radiologists routinely analyze hippocampal asymmetries in magnetic resonance (MR) images as a biomarker for neurodegenerative conditions like epilepsy and Alzheimer’s Disease. However, current clinical tools rely on either subjective evaluations, basic volume measurements, or disease-specific models that fail to capture more complex [...]
Gisela Pattarone, Laura Acion, Marina Simian, Emmanuel Iarussi
Automated cell classification in cancer biology is a challenging topic in computer vision and machine learning research. Breast cancer is the most common malignancy in women that usually involves phenotypically diverse populations of breast cancer cells and an heterogeneous stroma. In recent years, automated microscopy technologies are allowing the study of live cells over extended periods of time [...]
José Pablo Navarro, José Ignacio Orlando, Claudio Delrieux, Emmanuel Iarussi
Finding point-wise correspondences between images is a long-standing problem in computer vision. Corresponding sketch images is particularly challenging due to the varying nature of human style, projection distortions and viewport changes. In this paper we present a feature descriptor targeting line drawings [...]
Emmanuel Iarussi, Felix Thomsen, Claudio Delrieux
Research in vertebral bonemicro-structure generally requires costly procedures to obtain physical scans of real bone with a pathology under study, since no methods are available yet to generate realistic bone structures in-silico. Here we propose to apply recent advances in generative adversarial networks (GANs) to develop such a method. We adapted style-transfer techniques [...]
Santiago Vitale, José Ignacio Orlando, Emmanuel Iarussi, Ignacio Larrabide,
In this paper we propose to apply generative adversarial neural networks trained with a cycle-consistency loss, or CycleGANs, to improve realism in ultrasound (US) simulation from Computed Tomography (CT) scans. A ray-casting US simulation approach is used to generate intermediate synthetic images [...]
Luigi Malomo, Jesús Pérez, Emmanuel Iarussi, Nico Pietroni, Eder Miguel, Paolo Cignoni, Bernd Bickel
We propose FlexMaps, a novel framework for fabricating smooth shapes out of flat, flexible panels with tailored mechanical properties. We start by mapping the 3D surface onto a 2D domain as in traditional UV mapping to design a set of deformable flat panels called FlexMaps. For these panels [...]
Kazutaka Nakashima , Thomas Auzinger, Emmanuel Iarussi, Ran Zhang, Takeo Igarashi, Bernd Bickel
Molding is a popular mass production method, in which the initial expenses for the mold are offset by the low per-unit production cost. However, the physical fabrication constraints of the molding technique commonly restrict the shape of moldable objects. For a complex shape, a decomposition of the object into moldable parts is a common strategy [...]
Emmanuel Iarussi, Wilmot Li, Adrien Bousseau
Wire wrapping is a traditional form of handmade jewelry that involves bending metal wire to create intricate shapes. The technique appeals to novices and casual crafters because of its low cost, accessibility and unique aesthetic. We present a computational design tool that addresses the two main challenges of creating 2D wirewrapped [...]
Emmanuel Iarussi, David Bommes, Adrien Bousseau
Designers frequently draw curvature lines to convey bending of smooth surfaces in concept sketches. We present a method to extrapolate curvature lines in a rough concept sketch, recovering the intended 3D curvature field and surface normal at each pixel of the sketch. This 3D information allows us to enrich the sketch with 3D-looking shading [...]
Emmanuel Iarussi, Adrien Bousseau, Theophanis Tsandilas
We present an interactive drawing tool that provides automated guidance over model photographs to help people practice traditional drawing-by-observation techniques. The drawing literature describes a number of techniques to support this task and help people gain consciousness of the shapes in a scene and their relationships. We compile these techniques and derive a set of construction lines that we automatically extract from a model [...]
Drawing is the earliest form of visual depiction. The goal of this thesis is to facilitate and accelerate drawing for amateurs as well as for expert designers and illustrators, employing computer graphics, image processing and interaction techniques. As this is a broad spectrum to tackle, we identify three specific problems related to drawing and propose computer tools to help users overcome the main challenges on each domain [...]