H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science D-index 30 Citations 7,278 53 World Ranking 8668 National Ranking 4055

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Computer vision
  • Machine learning

Evangelos Kalogerakis mainly focuses on Artificial intelligence, Computer vision, Pattern recognition, Polygon mesh and Representation. His Artificial intelligence and Object, Benchmark, Active shape model, Graphical model and Image segmentation investigations all form part of his Artificial intelligence research activities. His Benchmark research includes themes of Segmentation, Scale-space segmentation and Conditional random field.

His work on Gesture recognition as part of general Computer vision research is often related to Orientation, Wearable computer and Set, thus linking different fields of science. His work on Hidden Markov model as part of his general Pattern recognition study is frequently connected to Prior probability, Matching and Forward–backward algorithm, thereby bridging the divide between different branches of science. His Representation research incorporates elements of Voxel, Convolutional neural network and Solid modeling.

His most cited work include:

  • Multi-view Convolutional Neural Networks for 3D Shape Recognition (1105 citations)
  • Learning hatching for pen-and-ink illustration of surfaces (561 citations)
  • Learning 3D mesh segmentation and labeling (408 citations)

What are the main themes of his work throughout his whole career to date?

Evangelos Kalogerakis spends much of his time researching Artificial intelligence, Computer vision, Segmentation, Pattern recognition and Point cloud. His work on Representation, Shape analysis and Convolutional neural network as part of general Artificial intelligence research is frequently linked to Context, bridging the gap between disciplines. His Computer vision research incorporates themes from Function, Animation, Polygon mesh and Sketch.

His work investigates the relationship between Polygon mesh and topics such as Rendering that intersect with problems in Curvature. The Segmentation study combines topics in areas such as Object and Benchmark. His biological study spans a wide range of topics, including Geometric primitive, Algorithm, Point and Feature learning.

He most often published in these fields:

  • Artificial intelligence (70.13%)
  • Computer vision (33.77%)
  • Segmentation (28.57%)

What were the highlights of his more recent work (between 2019-2021)?

  • Artificial intelligence (70.13%)
  • Point cloud (20.78%)
  • Segmentation (28.57%)

In recent papers he was focusing on the following fields of study:

The scientist’s investigation covers issues in Artificial intelligence, Point cloud, Segmentation, Algorithm and Geometric primitive. The various areas that Evangelos Kalogerakis examines in his Artificial intelligence study include Structure, Computer vision and Character. His Segmentation study necessitates a more in-depth grasp of Pattern recognition.

His work on Feature learning as part of general Pattern recognition research is frequently linked to Downstream and SIGNAL, bridging the gap between disciplines. His study looks at the intersection of Algorithm and topics like Parametric surface with Class. Point connects with themes related to Shape analysis in his study.

Between 2019 and 2021, his most popular works were:

  • MakeltTalk: speaker-aware talking-head animation (9 citations)
  • RigNet: neural rigging for articulated characters (6 citations)
  • Learning Part Boundaries from 3D Point Clouds (4 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Machine learning
  • Computer vision

His scientific interests lie mostly in Geometric primitive, Point cloud, Animation, Artificial intelligence and Algorithm. His Geometric primitive research is multidisciplinary, incorporating elements of Point, Segmentation, Boundary and 3D modeling. His work deals with themes such as Shape analysis and Pattern recognition, which intersect with Point cloud.

His studies in Animation integrate themes in fields like Representation, Character, Structure, Computer vision and Skeleton. Evangelos Kalogerakis integrates many fields, such as Artificial intelligence and Class, in his works. His Algorithm research is multidisciplinary, incorporating perspectives in Class and Parametric surface, Surface.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Multi-view Convolutional Neural Networks for 3D Shape Recognition

Hang Su;Subhransu Maji;Evangelos Kalogerakis;Erik Learned-Miller.
international conference on computer vision (2015)

1422 Citations

Learning 3D mesh segmentation and labeling

Evangelos Kalogerakis;Aaron Hertzmann;Karan Singh.
international conference on computer graphics and interactive techniques (2010)

567 Citations

Learning hatching for pen-and-ink illustration of surfaces

Evangelos Kalogerakis;Derek Nowrouzezahrai;Simon Breslav;Aaron Hertzmann.
ACM Transactions on Graphics (2012)

561 Citations

SPLATNet: Sparse Lattice Networks for Point Cloud Processing

Hang Su;Varun Jampani;Deqing Sun;Subhransu Maji.
computer vision and pattern recognition (2018)

368 Citations

A probabilistic model for component-based shape synthesis

Evangelos Kalogerakis;Siddhartha Chaudhuri;Daphne Koller;Vladlen Koltun.
international conference on computer graphics and interactive techniques (2012)

353 Citations

RisQ: recognizing smoking gestures with inertial sensors on a wristband

Abhinav Parate;Meng-Chieh Chiu;Chaniel Chadowitz;Deepak Ganesan.
international conference on mobile systems, applications, and services (2014)

260 Citations

Probabilistic reasoning for assembly-based 3D modeling

Siddhartha Chaudhuri;Evangelos Kalogerakis;Leonidas Guibas;Vladlen Koltun.
international conference on computer graphics and interactive techniques (2011)

257 Citations

3D Shape Segmentation with Projective Convolutional Networks

Evangelos Kalogerakis;Melinos Averkiou;Subhransu Maji;Siddhartha Chaudhuri.
computer vision and pattern recognition (2017)

213 Citations

Image sequence geolocation with human travel priors

Evangelos Kalogerakis;Olga Vesselova;James Hays;Alexei A. Efros.
international conference on computer vision (2009)

197 Citations

Coupling Ontologies with Graphics Content for Knowledge Driven Visualization

E. Kalogerakis;S. Christodoulakis;N. Moumoutzis.
ieee virtual reality conference (2006)

139 Citations

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