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The Neurally-Guided Shape Parser: A Monte Carlo Method for Hierarchical Labeling of Over-segmented 3D Shapes


Jun 22, 2021
R. Kenny Jones, Rana Hanocka, Daniel Ritchie


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ShapeMOD: Macro Operation Discovery for 3D Shape Programs


Apr 13, 2021
R. Kenny Jones, David Charatan, Paul Guerrero, Niloy J. Mitra, Daniel Ritchie

* Project Page: https://rkjones4.github.io/shapeMOD.html 

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Shape From Tracing: Towards Reconstructing 3D Object Geometry and SVBRDF Material from Images via Differentiable Path Tracing


Dec 06, 2020
Purvi Goel, Loudon Cohen, James Guesman, Vikas Thamizharasan, James Tompkin, Daniel Ritchie

* Will be published at 3DV 2020 

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Learning to Infer Shape Programs Using Latent Execution Self Training


Nov 25, 2020
Homer Walke, R. Kenny Jones, Daniel Ritchie

* 15 pages, 16 figures 

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ShapeAssembly: Learning to Generate Programs for 3D Shape Structure Synthesis


Sep 17, 2020
R. Kenny Jones, Theresa Barton, Xianghao Xu, Kai Wang, Ellen Jiang, Paul Guerrero, Niloy J. Mitra, Daniel Ritchie

* Accepted to Siggraph Asia 2020; project page: https://rkjones4.github.io/shapeAssembly.html 

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GANHopper: Multi-Hop GAN for Unsupervised Image-to-Image Translation


Feb 29, 2020
Wallace Lira, Johannes Merz, Daniel Ritchie, Daniel Cohen-Or, Hao Zhang

* 9 pages, 9 figures 

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Fast and Flexible Indoor Scene Synthesis via Deep Convolutional Generative Models


Nov 29, 2018
Daniel Ritchie, Kai Wang, Yu-an Lin


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Learning to Infer Graphics Programs from Hand-Drawn Images


Oct 26, 2018
Kevin Ellis, Daniel Ritchie, Armando Solar-Lezama, Joshua B. Tenenbaum


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Improving Shape Deformation in Unsupervised Image-to-Image Translation


Aug 13, 2018
Aaron Gokaslan, Vivek Ramanujan, Daniel Ritchie, Kwang In Kim, James Tompkin


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ScanComplete: Large-Scale Scene Completion and Semantic Segmentation for 3D Scans


Mar 28, 2018
Angela Dai, Daniel Ritchie, Martin Bokeloh, Scott Reed, Jürgen Sturm, Matthias Nießner

* Video: https://youtu.be/5s5s8iH0NF8 

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An Improved Training Procedure for Neural Autoregressive Data Completion


Nov 23, 2017
Maxime Voisin, Daniel Ritchie


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Deep Amortized Inference for Probabilistic Programs


Oct 18, 2016
Daniel Ritchie, Paul Horsfall, Noah D. Goodman


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Neurally-Guided Procedural Models: Amortized Inference for Procedural Graphics Programs using Neural Networks


Oct 13, 2016
Daniel Ritchie, Anna Thomas, Pat Hanrahan, Noah D. Goodman

* Neural Information Processing Systems (NIPS 2016) 

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C3: Lightweight Incrementalized MCMC for Probabilistic Programs using Continuations and Callsite Caching


Sep 08, 2015
Daniel Ritchie, Andreas Stuhlmüller, Noah D. Goodman

* Fix typo in author name 

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