Emmanuel Iarussi

#graphics #imaging #AI

Short Bio Welcome! I'm a Computer Scientist at CONICET, 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.


MAR 2021

I'll be the opener speaker at the Toronto Geometry Colloquium on March, 24th. More info here.

JAN 2021

I've joined the LatinX in CV (LXCV) Workshop as Sponsor & Finance Chair at CVPR 2021 .

DEC 2020

Our paper: SketchZooms: Deep multi-view descriptors for matching line drawings has been accepted to Computer Graphics Forum .

NOV 2020

Our project: Bone-GAN: Towards an accurate diagnosis of osteoporosis from routine body CTs has been granted with 50.000 USD from Salesforce Research AI. More details at Celebrating the Winners of the Third Annual Salesforce AI Research Grant.


SketchZooms: Deep multi-view descriptors for matching line drawings Computer Graphics Forum Wiley, 2021

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 [...]

Learning deep features for dead and living breast cancer cell classification without staining Nature Scientific Reports, 2021

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 [...]

Generative Modelling of 3D in-silico Spongiosa with Controllable Micro-Structural Parameters International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI) (pp. 785-794). Springer, Cham, 2020.

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 [...]

Improving realism in patient-specific abdominal Ultrasound simulation using CycleGANs International Journal of Computer Assisted Radiology and Surgery (pp. 1-10), 2019

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 [...]

FlexMaps: Computational Design of Flat Flexible Shells for Shaping 3D Objects SIGGRAPH ASIA 2018 ACM Transactions on Graphics (TOG)

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 [...]

CoreCavity: Interactive Shell Decomposition for Fabrication with Two-Piece Rigid Molds SIGGRAPH 2018 ACM Transactions on Graphics (TOG)

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 [...]

WrapIt: Computer-Assisted Crafting of Wire Wrapped Jewelry SIGGRAPH ASIA 2015 ACM Transactions on Graphics (TOG)

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 [...]

BendFields: Regularized Curvature Fields from Rough Concept Sketches SIGGRAPH 2015 ACM Transactions on Graphics (TOG)

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 [...]

The Drawing Assistant: Automated Drawing Guidance and Feedback from Photographs ACM UIST

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 [...]

Computer Drawing Tools for Assisting Learners, Hobbyists, and Professionals PhD. Thesis - Université de Nice

Emmanuel Iarussi

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 [...]