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Interactive Design of Developable Surfaces

We present a new approach to geometric modeling with developable surfaces and the design of curved-creased origami. We represent developables as splines and express the nonlinear conditions relating to developability and curved folds as quadratic equations. This allows us to utilize a constraint solver, which may be described as energy-guided... (more)

Matching Real Fabrics with Micro-Appearance Models

Micro-appearance models explicitly model the interaction of light with microgeometry at the fiber scale to produce realistic appearance. To... (more)

Interactive Acoustic Transfer Approximation for Modal Sound

Current linear modal sound models are tightly coupled with their frequency content. Both the modal vibration of object surfaces and the resulting... (more)

3D Mesh Labeling via Deep Convolutional Neural Networks

This article presents a novel approach for 3D mesh labeling by using deep Convolutional Neural Networks (CNNs). Many previous methods on 3D mesh... (more)

Pushing the Limits of 3D Color Printing

Accurate color reproduction is important in many applications of 3D printing, from design prototypes to 3D color copies or portraits. Although full color is available via other technologies, multi-jet printers have greater potential for graphical 3D printing, in terms of reproducing complex appearance properties. However, to date these printers... (more)

Vector Regression Functions for Texture Compression

Raster images are the standard format for texture mapping, but they suffer from limited resolution. Vector graphics are resolution-independent but are... (more)

Extraction of the Quad Layout of a Triangle Mesh Guided by Its Curve Skeleton

Starting from the triangle mesh of a digital shape, that is, mainly an articulated object, we produce a coarse quad layout that can be used in... (more)

Fast 4D Sheared Filtering for Interactive Rendering of Distribution Effects

Soft shadows, depth of field, and diffuse global illumination are common distribution effects, usually rendered by Monte Carlo ray tracing. Physically... (more)

Q-MAT

The medial axis transform (MAT) is an important shape representation for shape approximation, shape recognition, and shape retrieval. Despite years of research, there is still a lack of effective methods for efficient, robust and accurate computation of the MAT. We present an efficient method, called Q-MAT, that uses quadratic error minimization to... (more)

Predicting Appearance from Measured Microgeometry of Metal Surfaces

The visual appearance of many materials is created by micro-scale details of their surface geometry. In this article, we investigate a new approach to... (more)

Nonsmooth Developable Geometry for Interactively Animating Paper Crumpling

We present the first method to animate sheets of paper at interactive rates, while automatically... (more)

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About TOG

ACM TOG is the foremost peer-reviewed journal in the area of computer graphics. 

Recent impact factor calculations from Thomson Reuters give ACM TOG an impact factor of 4.096 and an Eigenfactor Score of 0.029, giving it the top ranking among the 104 journals in the Computer Science: Software Engineering category. 

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Forthcoming Articles
Efficient 3D Object Segmentation from Densely Sampled Light Fields with Applications to 3D Reconstruction

We present an efficient algorithm to automatically segment a static foreground object from highly cluttered background in light fields. A key insight and contribution of our paper is that a significant increase of the available input data can enable the design of novel, highly efficient approaches. In particular, the central idea of our method is to exploit high spatio-angular sampling on the order of thousands of input frames, e.g. captured as a hand-held video, such that new structures are revealed due to the increased coherence in the data. We first show how purely local gradient information contained in slices of such a dense light field can be combined with information about the camera trajectory to make efficient estimates of the foreground and background. These estimates are then propagated to textureless regions using edge-aware filtering in the epipolar volume. Finally, we enforce global consistency in a gathering step to derive a precise object segmentation both in 2D and 3D space, which captures fine geometric details even in very cluttered scenes. We demonstrate how the results of our method can be used for considerably improving the speed and quality of image-based 3D reconstruction algorithms, and we compare our results to state-of-the-art segmentation and multi-view stereo methods.

Automatic Photo Adjustment Using Deep Neural Networks

Photo retouching enables photographers to invoke dramatic visual impressions by artistically enhancing their photos through stylistic color and tone adjustments. However, it is also a time-consuming and challenging task that requires advanced skills beyond the abilities of casual photographers. Using an automated algorithm is an appealing alternative to manual work but such an algorithm faces many hurdles. Many photographic styles rely on subtle adjustments that depend on the image content and even its semantics. Further, these adjustments are often spatially varying. Because of these characteristics, existing automatic algorithms are still limited and cover only a subset of these challenges. Recently, deep machine learning has shown abilities to address hard problems that resisted machine algorithms for long. In this paper, we explain how to formulate the automatic photo adjustment problem using deep learning. We also introduce an image descriptor that accounts for the local semantics of an image. Our experiments demonstrate that our deep learning formulation applied using these descriptors successfully capture sophisticated photographic styles. In particular and unlike previous techniques, it can model local adjustments that depend on the image semantics. We show on several examples that this yields results that are qualitatively and quantitatively better than previous work.

Construction of Manifolds via Compatible Sparse Representations

Manifold is an important technique to model geometric objects with arbitrary topology. In this paper, we propose a novel approach for constructing manifolds from discrete meshes based on sparse optimization. The local geometry for each chart is sparsely represented by a set of redundant atom functions, which have the flexibility to represent various geometries with varying smoothness. A global optimization is then proposed to guarantee compatible sparse representations in the overlapping regions of different charts. Our method can construct manifolds of varying smoothness including sharp features (creases, darts, or cusps). As an application, we can easily construct a skinning manifold surface from a given curve network. Examples show that our approach has much flexibility to generate manifold surfaces with good quality.

Reconciling Elastic and Equilibrium Methods for Static Analysis

We examine two widely used classes of methods for static analysis of masonry buildingsfinite element and equilibrium methods. It is often claimed in the literature that finite element analysis is less accurate than equilibrium analysis when it comes to masonry analysis; we examine and qualify this claimed inaccuracy, provide a systematic explanation for the discrepancy observed between their results, and present a unified formulation of the two approaches to stability analysis. We prove that both approaches can be viewed as equivalent, dual methods for getting the same answer to the same problem. We validate our observations with simulations and physical tilt experiments of structures.

Interactively Cutting and Constraining Vertices in Meshes using Augmented Matrices

We present a finite element solution method for interactively cutting meshes in the regime of linear elastic models. Our approach features fast updates to the solution of the stiffness system of equations to account for real-time changes in mesh connectivity and boundary conditions. Updates are accomplished by augmenting the stiffness matrix to keep it consistent with the changes to the underlying model, without re-factoring the matrix at each step of cutting. The initial stiffness matrix and its Cholesky factors are used to implicitly form and solve a Schur complement system using an iterative solver. We exploit sparsity in the stiffness matrix, the right-hand-side vectors and the solution vectors to compute the solutions fast, and show that the time complexity of the update steps is bounded linearly by the size of the Cholesky factor of the initial matrix. Results for cutting and deformation of 3D linear elastic models are reported for meshes representing the brain, eye, and model problems with up to 167,000 elements; these show the potential of this method for real-time interactivity. An application to limbal incisions for surgical correction of astigmatism, where linear elastic models and small deformations are sufficient, is included.

Fairy Lights in Femtoseconds: Aerial and Volumetric Graphics Rendered by Focused Femtosecond Laser Combined with Computational Holographic Fields

We present a method of rendering aerial and volumetric graphics using femtosecond lasers. A high-intensity laser excites a physical matter to emit light at an arbitrary 3D position. Popular applications can then be explored especially since plasma induced by a femtosecond laser is safer than that generated by a nanosecond laser. The holograms and workspace of the system proposed here occupy a volume of up to 1 cm^3; however, this size is scalable depending on the optical devices and their setup. This paper provides details of the principles, system setup, and experimental evaluation, and discussions on scalability, design space, and applications of this system including tangible interaction. We tested two laser sources: an adjustable (30-100 fs) laser which projects up to 1,000 pulses per second at an energy up to 7 mJ per pulse, and a 269-fs laser which projects up to 200,000 pulses per second at an energy up to 50 ¼J per pulse. We confirmed that the spatiotemporal resolution of volumetric displays, implemented with these laser sources, is 4,000 and 200,000 dots per second. Although we focus on laser-induced plasma in air, the discussion presented here is also applicable to other rendering principles such as fluorescence and microbubble in solid/liquid materials.

Simit: A Language for Physical Simulation

Using existing programming tools, writing high-performance simulation code is labor intensive and requires sacrificing readability and portability. The alternative is to prototype simulations in a high-level language like Matlab, thereby sacrificing performance. In this paper, we present Simit, a new language for physical simulations that lets the programmer view the system both as a linked data structure in the form of a hypergraph, and as a set of global vectors, matrices and tensors depending on what is convenient at any given time. Simit provides a novel assembly construct that makes it conceptually easy and computationally efficient to move between the two abstractions. Using the information provided by the assembly construct, the compiler generates efficient in-place computation on the graph. We demonstrate that Simit is easy to use: a Simit program is typically shorter than a Matlab program; that it is high-performance: a Simit program running sequentially on a CPU performs comparably to hand-optimized simulations; and that it is portable: Simit programs can be compiled for GPUs with no change to the program, delivering 5-25x speedups over our optimized CPU code.

Occluded Imaging with Time of Flight Sensors

We explore the question of whether phase based Time of Flight (ToF) range cameras can be used for looking around corners and through scattering diffusers. By connecting time of flight measurements with theory from array signal processing we conclude that performance depends on two primary factors: camera modulation frequency and the width of the specular lobe (shininess) of the wall. For purely Lambertian walls, commodity time of flight sensors achieve resolution on the order of meters between targets. For seemingly diffuse walls, such as posterboard, the resolution is drastically reduced, to the order of ten centimeters. In particular, we find that the relationship between reflectance and resolution is nonlineara slight amount of shininess can lead to a dramatic improvement in resolution. Since many realistic scenes exhibit a slight amount of shininess we believe that off-theshelf ToF cameras can look around corners.

My Text in Your Handwriting

There are many scenarios where we wish to imitate a specific author's pen-on-paper handwriting style. Rendering new text in someone's handwriting is difficult because natural handwriting is highly variable, yet follows both intentional and involuntary structure that makes a person's style self-consistent. The variability means that naive example-based texture synthesis can be conspicuously repetitive. We propose an algorithm that renders a desired input string in an author's handwriting. An annotated sample of the author's handwriting is required; the system is flexible enough that historical documents can usually be used with only a little extra effort. Experiments show that our glyph-centric approach, with learned parameters for spacing, line thickness, and pressure, produces novel images of handwriting that look hand-made to casual observers, even when printed on paper.

Reconstruction of personalized 3D face rigs from monocular video

We present a novel approach that automatically creates personalized high-quality 3D face rigs of actors from just monocular footage, e.g. vintage movies. Our rig is based on three distinct layers that allow for modelling the actors' facial shape and capturing their person-specific expressiveness at high fidelity, ranging from coarse-scale geometry to fine-scale detail, such as wrinkles. Our approach is based on a parametric shape prior that encodes a plausible sub-space of variation in identity and expression. Based on this prior, a coarse-scale reconstruction is obtained through a novel variational fitting approach. We represent person-specific idiosyncrasies not spanned in the restricted shape and expression sub-space by learning a set of medium-scale correctives and fine-scale skin detail is retrieved via shading-based refinement. We create a generative detail model by coupling both the medium and fine-scale detail layers with the parametric prior using a novel sparse linear regression formulation. Once reconstructed, we conveniently control all layers of the rig by low-dimensional expression parameters, as widely used by animation artists. We show captured and animated face rigs of several actors filmed in different formats e.g. YouTube footage, and show that they are useful for 3D animation and 2D video editing. Finally, we evaluate our approach qualitatively and quantitatively and compare to related state-of-the-art methods.

Parallel Inverse Kinematics for Multi-Threaded Architectures

In this article we present a parallel prioritized Jacobian based inverse kinematics algorithm for multi-threaded architectures. We solve damped least squares inverse kinematics using a parallel line search by identifying and sampling critical input parameters. Parallel competing execution paths are spawned for each parameter in order to select the optimum which minimizes the error criteria. Our algorithm is highly scalable and can handle complex articulated bodies at interactive frame rates. We show results on complex skeletons consisting of more than 600 degrees of freedom while being controlled using multiple end effectors. We implement the algorithm both on multi-core and GPU architectures and demonstrate how the GPU can further exploit fine-grain parallelism not directly available on a multi- core processor. Our implementations are 10  150 times faster compared to a state-of-art serial implementation while providing higher accuracy. We also demonstrate the scalability of the algorithm over multiple scenarios and explore the GPU implementation in detail.

Discrete Connection and Covariant Derivative for Vector Field Analysis and Design

In this paper, we introduce a discrete definition of connection on simplicial manifolds, involving closed-form continuous expressions within simplices and finite rotations across simplices. The finite-dimensional parameters of this connection are optimally computed by minimizing a quadratic measure of the deviation to the (discontinuous) Levi-Civita connection induced by the embedding of the input triangle mesh. From this discrete connection, a covariant derivative is constructed through exact differentiation, leading to analytical expressions for local integrals of first-order derivatives (such as divergence, curl and the Cauchy-Riemann operator), and for L2-based energies (such as the Dirichlet energy). We finally demonstrate the utility, flexibility, and accuracy of our discrete formulations for the design and analysis of vector, n-vector, and n-direction fields.

High Brightness HDR Projection Using Dynamic Freeform Lensing

Cinema projectors need to compete with home theatre displays in terms of image quality. High frame rate, spatial resolution and 3D are common features today, but even the most advanced cinema projectors lack contrast and more importantly high peak luminance, both of which are essential perceptual attributes of images appearing realistic. HDR image statistics suggest that the average image intensity in a controlled ambient viewing environment such as cinema can be as low as 1% for cinematic HDR content and not often higher than 18%, middle gray in photography. Traditional projection systems form images and colors by blocking the source light from a lamp, therefore attenuating between 99% and 82% of light. This inefficient use of light poses significant challenges for achieving higher peak luminance levels. We propose a new projector architecture built around commercially available components, in which light can be steered to form an image. The gain in system efficiency can significantly reduce projector cost and increase peak luminance beyond what is practically achievable with incumbent projector technologies. At the heart of this computational display technology is a new projector hardware design using phase-modulation in combination with a new optimization algorithm that is capable of on-the-fly computation of freeform lens surfaces.

Intrinsic Girth Function for Shape Processing

We introduce the intrinsic girth function (IGF), a scalar field on a manifold closed surface. For each point p on the surface, the value of the IGF at p is the length of the globally shortest geodesic path starting from and ending at p. Therefore, th IGF is defined intrinsically and captures geometric properties more globally than surface curvature but more locally than the geodesic centricity and eccentricity functions. The IGF is invariant under isometry, insensitive to mesh tessellations, and robust to geometric noises and local surface variations. We shall present the applications of the IGF to shape retrieval and identifying tip parts and tube/plate structures of 3D shapes. Computationally, we develop an efficient method for computing the IGF with an empirical complexity of O(n2 log n) time and O(n) space, where n is the number of vertices of a triangle mesh surface representing the input shape.

Bibliometrics

Publication Years 1982-2016
Publication Count 2605
Citation Count 68118
Available for Download 2603
Downloads (6 weeks) 40964
Downloads (12 Months) 309686
Downloads (cumulative) 2993663
Average downloads per article 1150
Average citations per article 26
First Name Last Name Award
Aseem Agarwala ACM Doctoral Dissertation Award (2006)
Narendra Ahuja ACM Fellows (1996)
Kurt B Akeley ACM Fellows (1996)
Ronald M Baecker ACM Fellows (2011)
Chandrajit L. Bajaj ACM Fellows (2009)
Alan H Barr ACM Fellows (1995)
Benjamin B Bederson ACM Distinguished Member (2011)
Kellogg S. Booth ACM Distinguished Member (2009)
ACM Senior Member (2009)
Alan H Borning ACM Fellows (2001)
Achi Brandt SIAM/ACM Prize in Computational Science and Engineering (2005)
Frederick Brooks ACM - IEEE CS Eckert-Mauchly Award (2004)
A. M. Turing Award (1999)
ACM AAAI Allen Newell Award (1994)
ACM Fellows (1994)
ACM Distinguished Service Award (1987)
William A.S. Buxton ACM Fellows (2008)
Stuart K. Card ACM Fellows (2000)
Bernard Chazelle ACM Fellows (1996)
Bing-Yu Chen ACM Senior Member (2011)
Michael F. Cohen ACM Fellows (2007)
Rob Cook ACM Fellows (1999)
Seth Cooper ACM Doctoral Dissertation Award (2011)
Diane Crawford ACM - Infosys Foundation Award in the Computing Sciences (2007)
Thomas DeFanti ACM Fellows (1994)
Outstanding Contribution to ACM Award (1988)
James Demmel ACM Paris Kanellakis Theory and Practice Award (2014)
ACM Fellows (1999)
David P Dobkin ACM Fellows (1997)
David S Ebert ACM Senior Member (2009)
David Eppstein ACM Fellows (2011)
Irfan A Essa ACM Senior Member (2008)
Daniel Fay ACM Fellows (2007)
Adam Finkelstein ACM Fellows (2014)
James D Foley ACM Fellows (1999)
David Forsyth ACM Fellows (2013)
Henry Fuchs ACM Fellows (1995)
Donald Greenberg ACM Fellows (1995)
Markus Gross ACM Fellows (2012)
Leonidas J Guibas ACM AAAI Allen Newell Award (2007)
ACM Fellows (1999)
Baining Guo ACM Fellows (2011)
John Guttag ACM Fellows (2006)
Pat Hanrahan ACM Fellows (2008)
David Harel ACM Software System Award (2007)
ACM Fellows (1994)
ACM Karl V. Karlstrom Outstanding Educator Award (1992)
Aaron Hertzmann ACM Distinguished Member (2015)
Derek Hoiem ACM Doctoral Dissertation Award (2008)
Hugues Hoppe ACM Fellows (2011)
Mark A Horowitz ACM Fellows (2003)
Warren A. Hunt ACM Distinguished Member (2015)
ACM Senior Member (2013)
Victoria L Interrante ACM Senior Member (2007)
Takeo Kanade ACM AAAI Allen Newell Award (2010)
ACM Fellows (1999)
Dina Katabi ACM Fellows (2013)
ACM Grace Murray Hopper Award (2012)
ACM Doctoral Dissertation Award (2003)
Donald E Knuth ACM Fellows (1994)
ACM Software System Award (1986)
A. M. Turing Award (1974)
ACM Grace Murray Hopper Award (1971)
Daphne Koller ACM - Infosys Foundation Award in the Computing Sciences (2007)
Marc Levoy ACM Fellows (2007)
Henry M Levy ACM Fellows (1996)
Ming C Lin ACM Fellows (2011)
Dinesh Manocha ACM Fellows (2009)
Michael Mitzenmacher ACM Fellows (2014)
J Nievergelt ACM Fellows (1995)
James F. O'Brien ACM Distinguished Member (2009)
Dan R Olsen ACM Fellows (2006)
Ming Ouhyoung ACM Senior Member (2007)
Franco P Preparata ACM Fellows (1995)
Ravi Ramamoorthi ACM Distinguished Member (2015)
Sandy Ressler ACM Senior Member (2009)
Jarek Rossignac ACM Senior Member (2013)
Holly E Rushmeier ACM Distinguished Member (2006)
David H Salesin ACM Fellows (2002)
Hanan Samet ACM Paris Kanellakis Theory and Practice Award (2011)
ACM Fellows (1996)
Micha Sharir ACM Fellows (1997)
Stuart Shieber ACM Fellows (2014)
Ben Shneiderman ACM Fellows (1997)
Jeremy Sugerman ACM Software System Award (2009)
Subhash Suri ACM Fellows (2010)
ACM Distinguished Member (2007)
Ivan Sutherland ACM Fellows (1994)
ACM Software System Award (1993)
A. M. Turing Award (1988)
Richard Szeliski ACM Fellows (2008)
Shang-Hua Teng ACM Fellows (2009)
Demetri Terzopoulos ACM Fellows (2007)
Matthew A Turk ACM Senior Member (2007)
Baba C Vemuri ACM Fellows (2009)
Jeffrey S Vetter ACM Distinguished Member (2012)
ACM Gordon Bell Prize (2010)
ACM Fellows (1996)
Jeffrey S Vitter ACM Distinguished Member (2012)
ACM Gordon Bell Prize (2010)
ACM Fellows (1996)
J Turner Whitted ACM Fellows (1995)
Eugene Zhang ACM Senior Member (2010)
Lixia Zhang ACM Fellows (2006)
Yuanyuan Zhou ACM Fellows (2013)
ACM Distinguished Member (2011)
Denis Zorin ACM Gordon Bell Prize (2010)
Michael J Zyda ACM Senior Member (2009)
Andries van Dam ACM Fellows (1994)
ACM Karl V. Karlstrom Outstanding Educator Award (1993)
Andries van Dam ACM Fellows (1994)
ACM Karl V. Karlstrom Outstanding Educator Award (1993)

First Name Last Name Paper Counts
Daniel Cohen-Or 80
Frédo Durand 69
Baining Guo 61
Hans Seidel 56
Wojciech Matusik 55
Markus Gross 54
Kun Zhou 48
Heungyeung Shum 43
Ravi Ramamoorthi 42
Niloy Mitra 37
Ramesh Raskar 33
Szymon Rusinkiewicz 32
Kavita Bala 31
Jessica Hodgins 31
Maneesh Agrawala 30
Doug James 29
Fabio Pellacini 29
Hugues Hoppe 29
James O'Brien 29
Eitan Grinspun 27
Pat Hanrahan 26
Mark Pauly 26
Alla Sheffer 26
Peter Wonka 26
Henrik Jensen 26
Steve Marschner 26
Jovan Popovíc 26
Zoran Popović 26
Leonidas Guibas 25
Hujun Bao 24
Takeo Igarashi 24
Dani Lischinski 23
Richard Szeliski 22
Mathieu Desbrun 22
Hanspeter Pfister 22
Shimin Hu 21
Greg Turk 21
Bernd Bickel 21
Yaron Lipman 21
Shree Nayar 20
Ronald Fedkiw 20
Michael Cohen 20
Wojciech Jarosz 20
Helmut Pottmann 19
Thomas Funkhouser 19
Olga Sorkine-Hornung 19
Oliver Deussen 19
Vladlen Koltun 19
Denis Zorin 19
Liyi Wei 19
Adam Finkelstein 19
David Salesin 19
Jan Kautz 19
Raanan Fattal 18
Aseem Agarwala 18
Derek Nowrouzezahrai 18
Jason Lawrence 18
George Drettakis 18
Peter Schröder 18
Wolfgang Heidrich 18
Tientsin Wong 18
Dinesh Pai 17
Pieter Peers 17
Yizhou Yu 17
Hao Zhang 17
Matthias Zwicker 17
Wilmot Li 17
Robert Bridson 16
C Liu 16
Olga Sorkine 16
Michiel Van De Panne 16
William Freeman 16
Paul Debevec 16
Stelian Coros 15
Jaakko Lehtinen 15
John Snyder 15
Johannes Kopf 15
Bernhard Thomaszewski 15
Christian Theobalt 15
Dinesh Manocha 14
Julie Dorsey 14
Xin Tong 14
Jinxiang Chai 14
Brian Curless 14
Chris Wojtan 14
Tomas Akenine-Möller 14
Marc Alexa 14
Ariel Shamir 14
Stephen Lin 14
Bruce Walter 14
Tobias Ritschel 14
Daniele Panozzo 13
Ilya Baran 13
Diego Nehab 13
Weiwei Xu 13
Sylvain Lefebvre 13
Marie Cani 13
Karol Myszkowski 13
Marc Levoy 13
Chikeung Tang 13
Carol O'Sullivan 13
Andrei Sharf 13
Jian Sun 13
Diego Gutierrez 13
Sylvain Paris 13
Yang Liu 13
Donald Greenberg 13
Tao Ju 12
Aaron Hertzmann 12
Huamin Wang 12
Andrew Selle 12
Jernej Barbič 12
Tony DeRose 12
Ming Lin 12
Hao Zhang 12
Leif Kobbelt 12
Eli Shechtman 12
Tim Weyrich 12
Craig Gotsman 12
Adrien Bousseau 12
Shuang Zhao 12
Toshiya Hachisuka 11
Wenping Wang 11
Jin Huang 11
Connelly Barnes 11
Yue Dong 11
Johannes Wallner 11
Douglas Lanman 11
Robert Sumner 11
Ladislav Kavan 11
Bruno Lévy 11
Jehee Lee 11
Baoquan Chen 11
Dan Goldman 11
Adrien Treuille 11
Gordon Wetzstein 10
Steven Seitz 10
Jiaya Jia 10
Rasmus Tamstorf 10
Kai Xu 10
Ulrich Pinkall 10
Eftychios Sifakis 10
Singbing Kang 10
Shinjiro Sueda 10
Matthias Hullin 10
Marc Stamminger 10
Tongyee Lee 10
John Hart 10
Yingqing Xu 10
Bedřich Beneš 10
Miguel Otaduy 10
Alec Jacobson 10
Jiaping Wang 10
Alexei Efros 10
Holly Rushmeier 10
Matthias Nießner 10
Wenzel Jakob 10
Markus Gross 10
Changxi Zheng 10
Pierre Alliez 10
Scott Schaefer 10
Hui Huang 10
Thabo Beeler 10
Yiying Tong 10
François Sillion 10
Matthew Fisher 10
Mathieu Desbrun 9
Rahul Narain 9
Adam Bargteil 9
Michael Kazhdan 9
Jue Wang 9
Rafał Mantiuk 9
Minglun Gong 9
Joe Warren 9
Baoquan Chen 9
Daniel Aliaga 9
Etienne Vouga 9
Timo Aila 9
Philip Dutré 9
Rui Wang 9
Nancy Pollard 9
Jarek Rossignac 9
Alexander Hornung 9
Nathan Carr 9
Hendrik Lensch 9
Sylvain Paris 9
Kayvon Fatahalian 9
Elmar Eisemann 9
Todd Zickler 8
Charles Loop 8
Chiwing Fu 8
Marcus Magnor 8
Pradeep Sen 8
Michael Gleicher 8
Derek Bradley 8
Edward Adelson 8
Michael Goesele 8
François Faure 8
Long Quan 8
Tomoyuki Nishita 8
Peter Belhumeur 8
Keenan Crane 8
Nuttapong Chentanez 8
Marco Tarini 8
Matt Uyttendaele 8
Phengann Heng 8
James Tompkin 8
Craig Donner 8
Cyril Soler 8
Michael Garland 8
Miloš Hašan 8
Vladimir Kim 8
Kalyan Sunkavalli 8
Qiming Hou 8
Hongbo Fu 8
Peter Sloan 8
Jaroslav Křivánek 8
KangKang Yin 8
Xin Tong 8
Piotr Didyk 8
Ping Tan 8
Ofir Weber 7
Michael Rubinstein 7
Linjie Luo 7
Shahram Izadi 7
Ravi Ramamoorthi 7
Felix Heide 7
Theodore Kim 7
David Bommes 7
Ayellet Tal 7
Matthias Müller 7
Victor Ostromoukhov 7
Mark Horowitz 7
Doug DeCarlo 7
Peter Shirley 7
Fernando De Goes 7
Michael Wimmer 7
John Hughes 7
Pitchaya Sitthi-amorn 7
Christopher Batty 7
John Owens 7
Andrew Adams 7
Ligang Liu 7
Nico Pietroni 7
Yoshinori Dobashi 7
Yotam Gingold 7
Karan Singh 7
Demetri Terzopoulos 7
Maks Ovsjanikov 7
Brian Barsky 7
David Forsyth 7
Oliver Van Kaick 7
Robert Sumner 7
Nils Thuerey 7
Carsten Dachsbacher 7
Hao Li 7
Abhijeet Ghosh 7
Daniel Vlasic 7
Jonathan Ragan-Kelley 7
Jörg Peters 7
William Mark 7
Paul Beardsley 7
Noam Aigerman 6
Michael Zollhöfer 6
Nicolas Ray 6
Emily Whiting 6
Okan Arikan 6
Erik Reinhard 6
Sungeui Yoon 6
Rachel McDonnell 6
Thorsten Thormählen 6
Max Wardetzky 6
Eugene Zhang 6
Leonard McMillan 6
Valerio Pascucci 6
Matthew Hirsch 6
Evangelos Kalogerakis 6
Roger Hersch 6
Ivo Ihrke 6
Chiewlan Tai 6
James Ferwerda 6
Kari Pulli 6
Hao Li 6
Yuting Ye 6
Ron Goldman 6
Thomas Funkhouser 6
Paolo Cignoni 6
Yonghao Yue 6
Chandrajit Bajaj 6
Elaine Cohen 6
David Dobkin 6
Bart Adams 6
Noah Snavely 6
Floraine Berthouzoz 6
Solomon Boulos 6
Mirela Ben Chen 6
Enrico Puppo 6
Zeev Farbman 6
Andrew Nealen 6
Mario Botsch 6
Petrik Clarberg 6
Tim Hawkins 6
Yongjoon Lee 6
Yaser Sheikh 6
Kurt Akeley 6
Joseph Teran 6
Ariel Shamir 6
Anat Levin 6
John Keyser 6
Marcel Campen 6
Frank Losasso 6
David Luebke 6
Danny Kaufman 6
Manuel Oliveira 6
Pedro Sander 6
Tamy Boubekeur 6
Boris Neubert 6
Xinguo Liu 6
Hyeongseok Ko 6
Brian Wyvill 6
Qixing Huang 6
Christoph Von Tycowicz 5
Dinesh Manocha 5
Igor Mordatch 5
Greg Ward 5
Nobuyuki Umetani 5
Makoto Okabe 5
Sofien Bouaziz 5
Moritz Bächer 5
John Anderson 5
David Harmon 5
Ren Ng 5
Jack Tumblin 5
Ravish Mehra 5
Alec Rivers 5
Klaus Hildebrandt 5
John Lewis 5
Florence Bertails-Descoubes 5
Shimin Hu 5
Justin Solomon 5
Saikit Yeung 5
Chongyang Ma 5
Joelle Thollot 5
Andreas Weber 5
Jonathantyler Moon 5
Jon Hasselgren, 5
Naga Govindaraju 5
Tobias Pfaff 5
Changxi Zheng 5
Stefan Jeschke 5
Graham Fyffe 5
Shai Avidan 5
David Levin 5
Yingge Qu 5
Reinhard Klein 5
Nicolas Holzschuch 5
Patrick Mullen 5
Min Kim 5
Martin Bokeloh 5
Olga Sorkine 5
Eugene Fiume 5
Michael Nielsen 5
David Cohen-Steiner 5
Honghua Li 5
Amit Agrawal 5
Aleksey Golovinskiy 5
Zhong Ren 5
Ying He 5
Bingyu Chen 5
Mingming Cheng 5
Seungyong Lee 5
Brian Guenter 5
Christian Schulz 5
Ken Museth 5
Jianyuan Min 5
Amir Vaxman 5
Pascal Barla 5
Sebastian Thrun 5
Gabriel Taubin 5
Ulf Assarsson 5
Niloy Mitra 5
Min Tang 5
Ashish Myles 5
Jianmin Zheng 5
Jacob Munkberg 5
Srinivasa Narasimhan 5
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Xiaohan Shi 5
Arno Zinke 5
Xin Tong 5
Adam Arbree 5
Carsten Dachsbacher 5
Youngjun Kim 5
Ramesh Raskar 5
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Lvdi Wang 5
Dongming Yan 5
Charles Zitnick 5
Stephen DiVerdi 5
Martin Kilian 5
Xin Sun 5
Nils Thürey 5
Philipp Slusallek 5
Yungyu Chuang 5
Yongliang Yang 5
Michael Wand 5
Paul Kry 5
Kai Hormann 5
Aaron Hertzmann 5
Cem Yuksel 5
Derek Bradley 5
Carsten Rother 5
Samuli Laine 5
Yushuen Wang 5
Jonathan Shewchuk 5
Johannes Schmid 5
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Junyong Noh 4
Jason Sewall 4
Qixing Huang 4
Pierre Laffont 4
Claude Knaus 4
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Kevin Egan 4
Ibraheem Alhashim 4
Daniel Sýkora 4
Jonathan Denning 4
Charles Han 4
Basile Audoly 4
Thomas Sederberg 4
Forrester Cole 4
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Barbara Solenthaler 4
Bo Sun 4
Robert Cook 4
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Xi Wang 4
Victor Zordan 4
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Leif Kobbelt 4
Anton Kaplanyan 4
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Robert Carroll 4
Jay Busch 4
Qionghai Dai 4
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Michael Schwarz 4
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Ari Rappoport 4
Libin Liu 4
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Tiberiu Popa 4
Tamal Dey 4
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Karan Singh 4
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Lee Markosian 4
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James Gregson 4
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Mira Dontcheva 4
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Ralph Martin 4
Weiwen Feng 4
Sunghee Lee 4
Manolis Savva 4
Ronen Basri 4
Li Xu 4
Adrian Jarabo 4
Antonio Criminisi 4
Aljoscha Smolic 4
Rodolfo Lima 4
Tianjia Shao 4
Sungyong Shin 4
Dan Olsen 4
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Uri Ascher 4
Rémi Ronfard 4
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Alexander Schiftner 4
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Shihao Wu 4
Ian McDowall 4
Zhili Chen 4
Lei Yang 4
Taipang Wu 4
Jun Mitani 4
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Taku Komura 4
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Chaohui Shen 4
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Ran Gal 4
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Michael Burns 4
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Jack Wang 4
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Ruizhen Hu 4
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Zhigang Deng 4
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Menglei Chai 4
Billy Chen 4
Yanyun Chen 4
Art Tevs 4
Simon Heinzle 4
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Ken Perlin 4
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Chen Greif 4
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Jie Tan 4
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Yin Li 4
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Jiawen Chen 4
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Mark Meyer 4
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Scott Hudson 4
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Bin Wang 4
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Abe Davis 3
David Cline 3
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Amitabh Varshney 3
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Steffen Weißmann 3
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Jun Wang 3
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Barry Joe 3
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Baining Guo 3
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Insung Ihm 3
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Lapfai Yu 3
Ken Anjyo 3
Paul Asente 3
Chen Cao 3
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Bo Ren 3
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Gang Zeng 3
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Ankit Mohan 3
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Liwen Hu 3
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Kun Xu 3
Ruofeng Tong 3
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Binhhuy Le 3
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Jehee Lee 3
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Xin Sun 3
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Lin Shi 3
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Lifeng Wang 3
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Chenglei Wu 3
C Liu 3
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Florian Hecht 3
Michael Holroyd 3
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Jian Sun 3
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Gordon Wetzstein 3
Jaewoo Seo 3
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Youyi Zheng 3
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Li Zhang 3
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Desai Chen 2
Ming Zou 2
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Lu Yuan 2
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Otmar Hilliges 2
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