2026 Andrea Tagliasacchi: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Computer Science	43	7873	7647	317	303	155	9638

Overview

Andrea Tagliasacchi is affiliated with Simon Fraser University in Canada and has contributed extensively to the fields of computer science and engineering. Their research primarily covers areas in computer vision, computational mechanics, artificial intelligence, and aerospace engineering.

The scientist's work frequently appears in prominent publication venues, including:

arXiv (Cornell University)
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
2021 IEEE/CVF International Conference on Computer Vision (ICCV)
ACM Transactions on Graphics
2022 International Conference on Robotics and Automation (ICRA)

Their research spans multiple subfields, such as:

Computer Vision and Pattern Recognition
Computational Mechanics
Computer Graphics and Computer-Aided Design
Artificial Intelligence
Aerospace Engineering

Key topics in Andrea Tagliasacchi's work include:

3D Shape Modeling and Analysis
Advanced Vision and Imaging
Computer Graphics and Visualization Techniques
Human Pose and Action Recognition
Generative Adversarial Networks and Image Synthesis
3D Surveying and Cultural Heritage
Advanced Numerical Analysis Techniques

Some of their recent papers are:

COTR: Correspondence Transformer for Matching Across Images, 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
Panoptic Neural Fields: A Semantic Object-Aware Neural Scene Representation, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Vector Neurons: A General Framework for SO(3)-Equivariant Networks, 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
Kubric: A scalable dataset generator, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Neural Descriptor Fields: SE(3)-Equivariant Object Representations for Manipulation, 2022, 2022 International Conference on Robotics and Automation (ICRA)

Andrea Tagliasacchi has collaborated frequently with several researchers, notably including:

Kwang Moo Yi
Daniel Rebain
Leonidas Guibas
Sara Sabour
David J. Fleet

Best Publications

Sparse iterative closest point

Sofien Bouaziz;Andrea Tagliasacchi;Mark Pauly

592
Citations
A Survey of Surface Reconstruction from Point Clouds

Matthew Berger;Andrea Tagliasacchi;Lee M. Seversky;Pierre Alliez

550
Citations
Point Cloud Skeletons via Laplacian Based Contraction

Junjie Cao;Andrea Tagliasacchi;Matt Olson;Hao Zhang

377
Citations
MobileNeRF: Exploiting the Polygon Rasterization Pipeline for Efficient Neural Field Rendering on Mobile Architectures

Unknown

374
Citations
Curve skeleton extraction from incomplete point cloud

Andrea Tagliasacchi;Hao Zhang;Daniel Cohen-Or

366
Citations
State of the Art in Surface Reconstruction from Point Clouds

Matthew Berger;Andrea Tagliasacchi;Lee M. Seversky;Pierre Alliez

363
Citations
OpenScene: 3D Scene Understanding with Open Vocabularies

Unknown

337
Citations
Panoptic Neural Fields: A Semantic Object-Aware Neural Scene Representation

Unknown

331
Citations
Kubric: A scalable dataset generator

Unknown

291
Citations
BSP-Net: Generating Compact Meshes via Binary Space Partitioning

Zhiqin Chen;Andrea Tagliasacchi;Hao Zhang

288
Citations
Mean Curvature Skeletons

Andrea Tagliasacchi;Ibraheem Alhashim;Matt Olson;Hao Zhang

281
Citations
COTR: Correspondence Transformer for Matching Across Images

Wei Jiang;Eduard Trulls;Jan Hosang;Andrea Tagliasacchi

267
Citations
3D skeletons: a state-of-the-art report

Andrea Tagliasacchi;Thomas Delame;Michela Spagnuolo;Nina Amenta

266
Citations
Neural Descriptor Fields: SE(3)-Equivariant Object Representations for Manipulation

Unknown

263
Citations
Robust articulated-ICP for real-time hand tracking

Andrea Tagliasacchi;Matthias Schröder;Anastasia Tkach;Sofien Bouaziz

256
Citations
Deformation-driven shape correspondence

H. Zhang;A. Sheffer;D. Cohen-Or;Q. Zhou

246
Citations
CvxNet: Learnable Convex Decomposition

Boyang Deng;Kyle Genova;Soroosh Yazdani;Sofien Bouaziz

234
Citations
NASA: Neural Articulated Shape Approximation

Boyang Deng;John P. Lewis;Timothy Jeruzalski;Gerard Pons-Moll

200
Citations
Novel View Synthesis with Diffusion Models

Unknown

198
Citations
Vector Neurons: A General Framework for SO(3)-Equivariant Networks

Congyue Deng;Or Litany;Yueqi Duan;Adrien Poulenard

193
Citations
ACNe: Attentive Context Normalization for Robust Permutation-Equivariant Learning

Weiwei Sun;Wei Jiang;Eduard Trulls;Andrea Tagliasacchi

178
Citations
Sphere-meshes for real-time hand modeling and tracking

Anastasia Tkach;Mark Pauly;Andrea Tagliasacchi

169
Citations
High-contrast computational caustic design

Yuliy Schwartzburg;Romain Testuz;Andrea Tagliasacchi;Mark Pauly

139
Citations
DeRF: Decomposed Radiance Fields

Daniel Rebain;Wei Jiang;Soroosh Yazdani;Ke Li

137
Citations
Partial intrinsic reflectional symmetry of 3D shapes

Kai Xu;Hao Zhang;Andrea Tagliasacchi;Ligang Liu

132
Citations
Prior Knowledge for Part Correspondence

Oliver van Kaick;Andrea Tagliasacchi;Oana Sidi;Hao Zhang

120
Citations

Frequent Co-Authors

Shahram Izadi Google (United States)

Hao Zhang Simon Fraser University

Sean Ryan Fanello Google (United States)

Mark Pauly École Polytechnique Fédérale de Lausanne

Geoffrey E. Hinton University of Toronto

Christian Theobalt Max Planck Institute for Informatics

Daniel Cohen-Or Tel Aviv University

Leonidas J. Guibas Stanford University

Christoph Rhemann Google (United States)

Vincent Lepetit École des Ponts ParisTech

External Links

Personal website of Andrea Tagliasacchi

If you think any of the details on this page are incorrect, let us know.

Related Online Degrees & Career Pathways

Exploring career opportunities with a computer science background can be both exciting and versatile. Many students start their journey with associates degrees online, which provide a strong foundation for entry-level IT roles and the option to transfer credits toward a bachelor's degree.

Budget concerns are common, but a wide range of cheap online colleges now make it possible for students to earn accredited degrees without overwhelming debt. These programs often offer flexibility, letting you balance your studies with work or family responsibilities.

Worried about your grades? There are best online colleges that accept low gpa, making advanced study more accessible than ever before. This opens up pathways for students who may not have excelled academically but are passionate about pursuing computer science.

Finally, diverse degrees unlock multiple career fields. For instance, many wonder what can you get with an environmental science degree; similarly, computer science graduates are in demand in industries ranging from healthcare to finance, as well as emerging tech fields.