Conditionally Accepted SIGGRAPH 2019 Technical Papers

Apologies for typos and the lack of a clear formatting, I copied pasted from other web sites without editing (Note: Partial List).

A System for Efficient 3D Printed Stop-Motion Face Animation
Rinat Abdrashitov, Alec Jacobson, Karan Singh
ACM Transactions on Graphics 2019 (conditionally accepted). 
Paper (coming soon). Link.

Compact Snapshot Hyperspectral Imaging with Diffracted Rotation
Daniel S. Jeon, Seung-Hwan Baek, Shinyoung Yi, Qiang Fu, Xiong Dun, Wolfgang Heidrich, Min H. Kim
Conditionally accepted to ACM Transactions on Graphics (Proc. SIGGRAPH 2019). Link.

Siyan Dong, Kai Xu*, Qiang Zhou, Andrea Tagliasacchi, Shiqing Xin, Matthias Nießner, Baoquan Chen*, “Multi-Robot Collaborative Dense Scene Reconstruction, ACM Transactions on Graphics (SIGGRAPH 2019), Conditionally Accepted. Link.

Poly-Spline Finite Element Method
Teseo Schneider, Jeremie Dumas, Xifeng Gao, Mario Botsch, Daniele Panozzo, Denis Zorin,
ACM Transaction on Graphics, 2019
[Paper] [Code] Link.

Deformation Capture via Soft and Stretchable Sensor Arrays
Oliver Glauser, Daniele Panozzo, Otmar Hilliges, Olga Sorkine-Hornung,
ACM Transaction on Graphics, 2019
[Paper] [Video] Link.
Seunghwan Lee, Kyoungmin Lee, Moonseok Park, and Jehee Lee,
Scalable Muscle-actuated Human Simulation and Control
ACM Transactions on Graphics (SIGGRAPH 2019), Conditionally Accepted. Link.
Hyperparameter Optimization in Black-box Image Processing using Differentiable Proxies
E. Tseng, F. Yu, Y. Yang, F. Mannan, K. St-Arnaud, D. Nowrouzezahrai, J.-F. Lalonde, and F. Heide
ACM Transactions on Graphics (SIGGRAPH), 2019. Link
Felix Heide, Matthew O’Toole, Kai Zang, David Lindell, Steven Diamond, Gordon Wetzstein
ACM TOG (upcoming at SIGGRAPH 2019). Link
Atlas Refinement with Bounded Packing Efficiency
Hao-Yu Liu, Xiao-Ming Fu, Chunyang Ye, Shuangming Chai, Ligang Liu
Conditionally accepted by ACM Transactions on Graphics (SIGGRAPH) 38(4), 2019. Link
Computational Peeling Art Design
Hao Liu*, Xiao-Teng Zhang*, Xiao-Ming Fu, Zhi-Chao Dong, Ligang Liu (*Joint first authors)
Conditionally accepted by ACM Transactions on Graphics (SIGGRAPH) 38(4), 2019. Link

SAGNet: Structure-aware Generative Network for 3D-Shape Modeling
ACM Transactions on Graphics (Proceedings of SIGGRAPH 2019)
Zhijie Wu, Xiang Wang, Di LinDani LischinskiDaniel Cohen-Or, Hui Huang. Link.

iMapper: Interaction-guided Scene Mapping from Monocular Videos
Aron Monszpart, Paul Guerrero, Duygu Ceylan, Ersin Yumer, Niloy J. Mitra
SIGGRAPH (Conditional accept) 2019. Link.

Designing Chain Reaction Contraptions from Causal Graphs
Robin Roussel, Marie-Paule Cani, Jean-Claude Léon, Niloy J. Mitra
SIGGRAPH (Conditional accept) 2019. Link.

 

Surface2Volume: Surface Segmentation Conforming
Assemblable Volumetric Partition.
Chrystiano Araújo*, Daniela Cabiddu*, Marco Attene, Marco Livesu,
Nicholas Vining, Alla Sheffer 
(* joint first authors)
ACM Transactions on Graphics (SIGGRAPH 2019, Los Angeles, USA)
conditionally accepted. Link.

Distortion-Free Wide-Angle Portraits on Camera Phones
YiChang Shih, Wei-Sheng Lai, and Chia-Kai Liang
ACM Trans. Graphics (Proc. SIGGRAPH) 2019. Conditionally accepted. Link.

Nicolas Bonneel, David Coeurjolly
SPOT: Sliced Partial Optimal Transport
ACM Transactions on Graphics (SIGGRAPH), July 2019 (Conditionally Accepted). Link.

On writing Talk Abstracts

Ever thought how to condense summarize your talk into 1-paragraph? Look no further, and make sure all of these items are in it:

  • Motivation:
    Why do we care about the problem and the results? If the problem isn’t obviously “interesting” it might be better to put motivation first; but if your work is incremental progress on a problem that is widely recognized as important, then it is probably better to put the problem statement first to indicate which piece of the larger problem you are breaking off to work on. This section should include the importance of your work, the difficulty of the area, and the impact it might have if successful.
  • Problem statement:
    What problem are you trying to solve? What is the scope of your work (a generalized approach, or for a specific situation)? Be careful not to use too much jargon. In some cases it is appropriate to put the problem statement before the motivation, but usually this only works if most readers already understand why the problem is important.
  • Approach:
    How did you go about solving or making progress on the problem? Did you use simulation, analytic models, prototype construction, or analysis of field data for an actual product? What was the extent of your work (did you look at one application program or a hundred programs in twenty different programming languages?) What important variables did you control, ignore, or measure?
  • Results:
    What’s the answer? Specifically, most good computer architecture papers conclude that something is so many percent faster, cheaper, smaller, or otherwise better than something else. Put the result there, in numbers. Avoid vague, hand-waving results such as “very”, “small”, or “significant.” If you must be vague, you are only given license to do so when you can talk about orders-of-magnitude improvement. There is a tension here in that you should not provide numbers that can be easily misinterpreted, but on the other hand you don’t have room for all the caveats.
  • Conclusions:
    What are the implications of your answer? Is it going to change the world (unlikely), be a significant “win”, be a nice hack, or simply serve as a road sign indicating that this path is a waste of time (all of the previous results are useful). Are your results general, potentially generalizable, or specific to a particular case?

 

Also, avoid emotional words like exciting.

Shamelessly copied from here

Cropping figures in latex

Image you have a figure, but it just needs a bit of tweaking. Fear not! the following will do all the magic for you:

\usepackage{graphicx}
...
\begin{figure}[htbp]
    \begin{center}
        \includegraphics[trim=left bottom right top, clip]{file}
    \caption{default}
    \label{default}
    \end{center}
\end{figure}

, where the default units of trim are big points (bp). For example:
trim=1200 400 1500 1500, clip]

I recommend you start small (say 100) and then go up from there, depending on the need.
Taken from here.

Partial list of Conditionally Accepted SIGGRAPH ASIA 2018 papers

Apologies for typos and the lack of a clear formatting, I copied pasted from other web sites without editing:

  • C. Li, H. Pan, Y. Liu, X. Tong, A. Sheffer, W. Wang,  Robust Flow-Guided Neural Prediction for Sketch-Based Freeform Surface Modeling , ACM Transactions on Graphics (Proc SIGGRAPH Asia) 2018, accepted. link
  • M Li, D. M. Kaufman, V. G. Kim, J. Solomon, A. ShefferOptCuts: Joint Optimization of Surface Cuts and Parameterization , ACM Transactions on Graphics (Proc SIGGRAPH Asia) 2018, accepted. link
  • Lavenant, Hugo, Sebastian Claici, Edward Chien, and Justin Solomon. “Dynamical Optimal Transport on Discrete Surfaces.” SIGGRAPH Asia 2018, Tokyo (to appear). link
  • GPU Optimization of Material Point Methods , Ming Gao*, Xinlei Wang*, Kui Wu* (equal contributions), Andre Pradhana-Tampubolon, Eftychios Sifakis, Cem Yuksel, Chenfanfu Jiang. link
  • Narrow-Band Topology Optimization on a Sparsely Populated Grid 
    Haixiang Liu*, Yuanming Hu* (joint first authors), Bo Zhu, Wojciech Matusik, Eftychios Sifakis. link
  • Deep Multispectral Painting Reproduction via Multi-layer, Custom-Ink Printing
    Liang Shi, Vahid Babaei, Changil Kim, Michael Foshey, Yuanming Hu, Pitchaya Sitthi-Amorn, Szymon Rusinkiewicz, Wojciech Matusik link
  • Guowei Yan, Wei Li, Ruigang Yang and Huamin Wang. 2018. Inexact Descent Methods for Elastic Parameter Optimization. ACM Transactions on Graphics (SIGGRAPH Asia), conditionally accepted. link
  • Multi-chart Generative Surface Modeling
    Heli Ben-Hamu, Haggai Maron, Itay Kezurer, Gal Avineri, Yaron Lipman
    Conditionally accepted to ACM SIGGRAPH Asia 2018. link
  • Chenyang Zhu, Kai Xu*, Siddhartha Chaudhuri, Renjiao Yi and Hao Zhang, “SCORES: Shape Composition with Recursive Substructure Priors, ACM Transactions on Graphics (SIGGRAPH Asia 2018), 37(6). link
  • Xiaogang Wang, Bin Zhou, Haiyue Fang, Xiaowu Chen, Qinping Zhao and Kai Xu*, “Learning to Group and Label Fine-Grained Shape Components, ACM Transactions on Graphics (SIGGRAPH Asia 2018), 37(6). Conditionally accepted. link
  • Hao Wang, Nadav Schor, Ruizhen Hu, Haibin Huang, Daniel Cohen-Or, Hui Huang
    Conditionally Accepted to ACM SIGGRAPH ASIA 2018
  • Li Yi, Haibin Huang, Difan Liu, Evangelos Kalogerakis, Hao Su, Leonidas Guibas
    Conditionally Accepted to ACM SIGGRAPH ASIA 2018
  • 3D Hair Synthesis Using Volumetric Variational Autoencoders
    Shunsuke Saito, Liwen Hu, Chongyang Ma, Hikaru Ibayashi, Linjie Luo, Hao Li link
  • N. Smith, N. Moehrle, M. Goesele, W. Heidrich:
    Aerial Path Planning for Urban Scene Reconstruction — A Continuous Optimization Method and Benchmark
    ACM Transactions on Graphics (Proc. SIGGRAPH Asia), 2018 link
  • Efficient palette-based decomposition and recoloring of images via RGBXY-space geometry
    Jianchao Tan, Jose Echevarria, Yotam Gingold
    ACM Transactions on Graphics (TOG) 37(6). To be presented at SIGGRAPH Asia 2018.  link
  • Modeling Hair from an RGB-D Camera
    Meng Zhang, Pan Wu, Hongzhi Wu, Yanlin Weng, Youyi Zheng, Kun Zhou
    ACM Transactions on Graphics (SIGGRAPH ASIA 2018) link

  • Warp-guided GANs for Single-Photo Facial Animation
    ACM Transactions on Graphics (SIGGRAPH ASIA 2018)
    Jiahao Geng, Tianjia Shao, Youyi Zheng, Yanlin Weng, Kun Zhou link

  • paGAN: Real-time Avatars Using Dynamic Textures
    Koki Nagano, Jaewoo Seo, Jun Xing, Lingyu Wei, Zimo Li, Shunsuke Saito, Aviral Agarwal, Jens Fursund, Hao Li
    ACM Transactions on Graphics (SIGGRAPH ASIA 2018)
    [Live Demo] [RTL] [FXGUIDE] link
  • CreativeAI: Deep Learning for Computer GraphicsNiloy J. Mitra, Iasonas Kokkinos, Paul Guerrero, Nils Thuerey, Tobias Ritschel conditionally accepted to SIGGRAPH Asia 2018 link
  • FrankenGAN: Guided Detail Synthesis for Building Mass-Models Using Style-Synchonized GANs
    Tom Kelly*, Paul Guerrero*, Anthony Steed, Peter Wonka^, Niloy J. Mitra^
    SIGGRAPH Asia 2018 link
  • Learning a Shared Shape Space for Multimodal Garment Design
    Tuanfeng Wang, Duygu Ceylan, Jovan Popovic, Niloy J. Mitra
    SIGGRAPH Asia 2018 link
  • Aerobatics Control of Flying Creatures via Self-Regulated Learning, SIGGRAPH Asia 2018.  Jehee Lee and colleagues. link
  • Interactive Character Animation by Learning Multi-Objective Control, SIGGRAPH Asia 2018. Jehee Lee and colleagues. link
  • Learning to Dress: Synthesizing Human Dressing Motion via Deep Reinforcement Learning, Alex Clegg, Wenhao Yu, Jie Tan, C. Karen Liu and Greg Turk, in Transactions on Graphics (SIGGRAPH Asia), 2018 [PDF]  [Video] link

  • “Hybrid Grains: Adaptive Coupling of Discrete and Continuum Simulations of Granular Media,” Yonghao Yue*, Breannan Smith*, Peter Yichen Chen*, Maytee Chantharayukhonthorn*, Ken Kamrin+, and Eitan Grinspun+ (*: co-first authors, +: corresponding authors). 2018. ACM Transactions on Graphics, Vol.37, No.6 (Proc. SIGGRAPH ASIA 2018). Tokyo, Japan. [PDF] [Video] [Bibtex] [Project] link
  • Hsueh-Ti Derek Liu, Michael Tao, Alec Jacobson. “Paparazzi: Surface Editing by way of Multi-View Image Processing” ACM Transactions on Graphics (Proc. SIGGRAPH Asia), 2018. link
  • “Geometry-Aware Metropolis Light Transport”
    H. Otsu, J. Hanika, T. Hachisuka, and C. Dachsbacher
    ACM Transactions on Graphics (SIGGRAPH Asia 2018), 2018 link
  • Mingming He, Dongdong Chen, Jing Liao, Pedro V. Sander, Lu Yuan.
    Deep Examplar-Based Colorization.
    ACM Transactions on Graphics (SIGGRAPH 2018) [conditionally accepted]. link
  • Multi-view Wire Art
    Kai-Wen Hsiao, Jia-Bin Huang, and Hung-Kuo Chu
    (Conditionally accepted)
    ACM Transactions on Graphics (Proceedings of SIGGRAPH Asia), 2018
    [Paper (PDF)] [Project page] [Code] link
  • Decoupling Simulation Accuracy from Mesh Quality
    Teseo Schneider, Yixin Hu, Jérémie Dumas, Xifeng Gao, Daniele Panozzo, Denis Zorin.
    ACM Transactions on Graphics (SIGGRAPH Asia 2018)
    [paper], [code(todo)]. link
  • SIGGRAPH Asia 2018

    pdf | webpage link

  • Stabilized Real-time Face Tracking via a Learned Dynamic Rigidity Prior
    ACM Transactions on Graphics (Proc. SIGGRAPH Asia), December 2018
    Chen Cao, Menglei Chai, Oliver Woodford and Linjie Luo.  link
  • George E. BrownMatthew OverbyZahra Forootaninia, and Rahul Narain.
    “Accurate Dissipative Forces in Optimization Integrators”.
    ACM Transactions on Graphics (Proc. SIGGRAPH Asia), 2018, to appear. link
  • Crowd Space: A Predictive Crowd Analysis Technique,
    Ioannis Karamouzas, Nick Sohre, Ran Hu, and Ioannis Karamouzas
    In SIGGRAPH Asia 2018 (to appear).
    [pdf] [bib] [project] link

Predatory journals

From Wikipedia: “Predatory open-access publishing is an exploitative open-access academic publishing business model that involves charging publication fees to authors without providing the editorial and publishing services associated with legitimate journals (open access or not). The idea that they are “predatory” is based on the view that academics are tricked into publishing with them, though some authors may be aware that the journal is poor quality or even fraudulent.”

Personally, I get a lot of spam email from these type of journals. This site keeps a list of such journals. That being said, because of such spam, I am not sure whether journals that I am unfamiliar with or are new are predatory or not:

Dear …,

We came across a very interesting article of yours:

….

On behalf of our Guest Editors Prof. Andrew Ware (University of South
Wales, UK) and Prof. Athanasios G. Malamos (Technological Educational
Institution of Crete, Greece), we would like to invite you to contribute
either a review or a research paper, to be published in the Special
Issue “Artificial Intelligence Supported Design and Innovation” of the
journal Designs (ISSN 2411-9660; http://www.mdpi.com/journal/designs).

*Special Issue Scope*
The primary objective of the Special Issue is to present a coherent and
comprehensive analysis of developments relating to the application of
artificial intelligent techniques in the field of design and innovation.
The topics include, but are not limited to the following: Creativity;
Intelligent design; Computer-aided design; Algorithm-driven design; UI
and UX design; Games design; Planning design; Personal Assistant systems
design; Optimization/evaluation in engineering design; Sensing and AI
signal processing and control; Cognitive design; Decision support; Deep
learning; Crowdsourcing design […]
More details about this Special Issue can be found at:
http://www.mdpi.com/journal/designs/special_issues/artificial_intelligence_Design

*Author Benefits*
Designs is one of MDPI’s open access journals, which covers all aspects
of *Engineering Designs* research. Our authors enjoy the benefits of:
1. *No charges* for well-prepared contributions; free English editing
service after acceptance;
2. Open access and high visibility: unlimited access, various
promotional activities and academic event presentations;
3. Rapid response from submission to first decision within approx. 3
weeks, publication within approx. 6 weeks;
4. No restrictions on the length of manuscripts.

The official deadline for full paper delivering is 20 *February* 2019.
You may submit your manuscript at any time until this deadline. Accepted
papers will be published immediately, and do not need to wait other
planned manuscripts.

Should you have any questions, please feel free to contact us. We look
forward to having a cooperation with you on this project. 🙂

Best regards,

Mr. Ryan Pei
Managing Editor, Designs

On behalf of Guest Editors

Prof. Dr. Andrew Ware
Faculty of Computing, Engineering and Science,
University of South Wales,
Pontypridd, CF37 1DL, UK

Prof. Dr. Athanasios G. Malamos
Multimedia, Networks and Communications Laboratory,
Department of Informatics Engineering,
Technological Educational Institution of Crete,
Estavromenos 71401, Heraklion Crete, Greece

MDPI, Designs Editorial Office
St. Alban-Anlage 66, 4052 Basel, Switzerland
Email: designs@mdpi.com
http://www.mdpi.com/journal/designs

 

 

Finding Duplicate Latex Labels

While working on a my dissertation, I noticed that LaTeX was giving me a warning message:
LaTeX Warning: There were multiply-defined labels.

Since LaTeX didn’t feel the need to tell me which labels were multiply-defined, I had to find them myself. Finding these by hand is hard to impossible. Luckily, this perl script solves the problem:

perl -nE 'say $1 if /(\\label[^}]*})/' *.tex | sort | uniq -c | sort -n

Taken from here.